{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/sambell/Dropbox/Bell_Kitagawa/JCR Draft/JCR R&R/Data/Creating some new variables in TJ data - side analysis/Replication.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 4 Nov 2021, 13:02:06
{txt}
{com}. 
. *table 1***
. 
. eststo: probit physint_imp physint_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_physint_imp_count time_physint_sq  time_physint_cub if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-1279.3501
{txt}Iteration 1:   log pseudolikelihood = {res}-1161.9655
{txt}Iteration 2:   log pseudolikelihood = {res}-1160.7347
{txt}Iteration 3:   log pseudolikelihood = {res}-1160.7342

{txt}Probit regression                                 Number of obs   = {res}      2041
                                                  {txt}Wald chi2({res}18{txt})   = {res}    251.59
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-1160.7342                 {txt}Pseudo R2       = {res}    0.0927

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
 physint_imp {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
 physint_lag {c |}  {res}-.2410108   .0242037    -9.96   0.000    -.2884492   -.1935723
{txt}domest~1_lag {c |}  {res} .0702332   .1248108     0.56   0.574    -.1743915    .3148579
{txt}domestick1.. {c |}  {res}-.0354299    .133847    -0.26   0.791    -.2977651    .2269053
 {txt}polity2_lag {c |}  {res} .0091713   .0099245     0.92   0.355    -.0102804     .028623
{txt}ln_gdppc_lag {c |}  {res}-.0267926   .0437131    -0.61   0.540    -.1124688    .0588836
{txt}ln_populat~g {c |}  {res}-.1655783   .0334552    -4.95   0.000    -.2311492   -.1000073
     {txt}lji_lag {c |}  {res}  .295787   .2939942     1.01   0.314     -.280431    .8720049
{txt}high_confl~t {c |}  {res}-.7647855   .1406429    -5.44   0.000    -1.040441   -.4891304
{txt}djamne~1_lag {c |}  {res}-.1246267   .1279154    -0.97   0.330    -.3753363    .1260829
 {txt}truthk1_lag {c |}  {res} .1736962   .1916295     0.91   0.365    -.2018906    .5492831
     {txt}cat_rat {c |}  {res}-.0688022   .0848692    -0.81   0.418    -.2351427    .0975383
    {txt}ccpr_rat {c |}  {res}-.2373785   .1016283    -2.34   0.020    -.4365664   -.0381906
      {txt}africa {c |}  {res}-.0795073   .1212296    -0.66   0.512     -.317113    .1580984
        {txt}asia {c |}  {res}-.2243995   .1365574    -1.64   0.100    -.4920471    .0432481
      {txt}europe {c |}  {res} .4210975   .1250162     3.37   0.001     .1760703    .6661246
{txt}time_physi~t {c |}  {res} .1716852   .0454346     3.78   0.000     .0826351    .2607353
{txt}time_physi~q {c |}  {res}-.0231634   .0086152    -2.69   0.007    -.0400488    -.006278
{txt}time_physi~b {c |}  {res}  .000755    .000295     2.56   0.010     .0001768    .0013332
       {txt}_cons {c |}  {res} 3.364145   .5452913     6.17   0.000     2.295394    4.432896
{txt}{hline 13}{c BT}{hline 64}
({res}est1{txt} stored)

{com}. 
. eststo: probit polpris_imp polpris_lag domestick1_lag domestick1_lag_two_yr  polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_polpris_count time_polpris_sq time_polpris_cub if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-856.47669
{txt}Iteration 1:   log pseudolikelihood = {res}-711.80103
{txt}Iteration 2:   log pseudolikelihood = {res}-704.60888
{txt}Iteration 3:   log pseudolikelihood = {res}-704.49358
{txt}Iteration 4:   log pseudolikelihood = {res}-704.49354

{txt}Probit regression                                 Number of obs   = {res}      2047
                                                  {txt}Wald chi2({res}18{txt})   = {res}    279.88
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-704.49354                 {txt}Pseudo R2       = {res}    0.1775

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
 polpris_imp {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
 polpris_lag {c |}  {res}-1.067671   .0831832   -12.84   0.000    -1.230707   -.9046351
{txt}domest~1_lag {c |}  {res} .4197454   .1462761     2.87   0.004     .1330496    .7064412
{txt}domestick1.. {c |}  {res}-.2947061   .2382076    -1.24   0.216    -.7615844    .1721721
 {txt}polity2_lag {c |}  {res} .0604445   .0124736     4.85   0.000     .0359966    .0848923
{txt}ln_gdppc_lag {c |}  {res} -.083431   .0624055    -1.34   0.181    -.2057436    .0388815
{txt}ln_populat~g {c |}  {res} -.205835   .0372744    -5.52   0.000    -.2788915   -.1327786
     {txt}lji_lag {c |}  {res} .1539858   .3466044     0.44   0.657    -.5253463     .833318
{txt}high_confl~t {c |}  {res}-.5062513    .168499    -3.00   0.003    -.8365034   -.1759992
{txt}djamne~1_lag {c |}  {res} .0787379   .1392977     0.57   0.572    -.1942805    .3517563
 {txt}truthk1_lag {c |}  {res} .3873393   .2730494     1.42   0.156    -.1478277    .9225062
     {txt}cat_rat {c |}  {res}-.0289602   .1081162    -0.27   0.789    -.2408641    .1829438
    {txt}ccpr_rat {c |}  {res}-.2824061   .1354461    -2.09   0.037    -.5478756   -.0169366
      {txt}africa {c |}  {res}-.1371499   .1637701    -0.84   0.402    -.4581333    .1838335
        {txt}asia {c |}  {res}-.4323279   .1541659    -2.80   0.005    -.7344876   -.1301683
      {txt}europe {c |}  {res} .2083657   .2237577     0.93   0.352    -.2301912    .6469227
{txt}time~s_count {c |}  {res}-.0495782   .0414439    -1.20   0.232    -.1308068    .0316504
{txt}time_po~s_sq {c |}  {res}  .000101   .0048665     0.02   0.983    -.0094372    .0096392
{txt}time_p~s_cub {c |}  {res} .0000386   .0001302     0.30   0.767    -.0002165    .0002938
       {txt}_cons {c |}  {res} 4.076877   .7640921     5.34   0.000     2.579284     5.57447
{txt}{hline 13}{c BT}{hline 64}
({res}est2{txt} stored)

{com}. 
. eststo: probit tort_imp tort_lag domestick1_lag domestick1_lag_two_yr  polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_tort_count time_tort_sq time_tort_cub if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-791.69708
{txt}Iteration 1:   log pseudolikelihood = {res}-682.68001
{txt}Iteration 2:   log pseudolikelihood = {res}-676.99347
{txt}Iteration 3:   log pseudolikelihood = {res}-676.91179
{txt}Iteration 4:   log pseudolikelihood = {res}-676.91176

{txt}Probit regression                                 Number of obs   = {res}      2054
                                                  {txt}Wald chi2({res}18{txt})   = {res}    245.94
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-676.91176                 {txt}Pseudo R2       = {res}    0.1450

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
    tort_imp {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
    tort_lag {c |}  {res}-1.078734   .0955346   -11.29   0.000    -1.265978   -.8914895
{txt}domest~1_lag {c |}  {res}-.2801001   .2074628    -1.35   0.177    -.6867197    .1265195
{txt}domestick1.. {c |}  {res}-.3562673    .165394    -2.15   0.031    -.6804336    -.032101
 {txt}polity2_lag {c |}  {res} .0066688   .0140647     0.47   0.635    -.0208976    .0342351
{txt}ln_gdppc_lag {c |}  {res} .0216979   .0577689     0.38   0.707    -.0915271    .1349229
{txt}ln_populat~g {c |}  {res}-.1494216   .0370797    -4.03   0.000    -.2220964   -.0767467
     {txt}lji_lag {c |}  {res} .6767216    .358514     1.89   0.059     -.025953    1.379396
{txt}high_confl~t {c |}  {res}-.3874762   .1749268    -2.22   0.027    -.7303263    -.044626
{txt}djamne~1_lag {c |}  {res}  .064271   .1405573     0.46   0.647    -.2112162    .3397583
 {txt}truthk1_lag {c |}  {res} .7154051   .2640246     2.71   0.007     .1979264    1.232884
     {txt}cat_rat {c |}  {res}-.2849871   .1007591    -2.83   0.005    -.4824712    -.087503
    {txt}ccpr_rat {c |}  {res}-.2222226   .1121234    -1.98   0.047    -.4419805   -.0024648
      {txt}africa {c |}  {res}  .114925   .1468807     0.78   0.434    -.1729559     .402806
        {txt}asia {c |}  {res}-.1460899   .1595791    -0.92   0.360    -.4588592    .1666795
      {txt}europe {c |}  {res} .4984459   .1634126     3.05   0.002     .1781631    .8187288
{txt}time~t_count {c |}  {res} -.045573   .0375181    -1.21   0.224    -.1191072    .0279611
{txt}time_tort_sq {c |}  {res}-.0005725   .0035742    -0.16   0.873    -.0075778    .0064328
{txt}time_~rt_cub {c |}  {res} .0000474   .0000935     0.51   0.612    -.0001359    .0002307
       {txt}_cons {c |}  {res}  1.83773   .7192454     2.56   0.011     .4280349    3.247425
{txt}{hline 13}{c BT}{hline 64}
({res}est3{txt} stored)

{com}. 
. eststo: probit kill_imp kill_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_kill_count time_kill_sq time_kill_cub if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-911.56311
{txt}Iteration 1:   log pseudolikelihood = {res}-778.89777
{txt}Iteration 2:   log pseudolikelihood = {res}-772.88171
{txt}Iteration 3:   log pseudolikelihood = {res}-772.81599
{txt}Iteration 4:   log pseudolikelihood = {res}-772.81598

{txt}Probit regression                                 Number of obs   = {res}      2052
                                                  {txt}Wald chi2({res}18{txt})   = {res}    192.06
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-772.81598                 {txt}Pseudo R2       = {res}    0.1522

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
    kill_imp {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
    kill_lag {c |}  {res}-.9594374   .0888275   -10.80   0.000    -1.133536   -.7853386
{txt}domest~1_lag {c |}  {res} .0247687   .1678803     0.15   0.883    -.3042707     .353808
{txt}domestick1.. {c |}  {res} -.039263   .1854315    -0.21   0.832    -.4027022    .3241761
 {txt}polity2_lag {c |}  {res}-.0533329   .0146362    -3.64   0.000    -.0820194   -.0246464
{txt}ln_gdppc_lag {c |}  {res}-.0731131   .0614152    -1.19   0.234    -.1934847    .0472585
{txt}ln_populat~g {c |}  {res}-.1623007   .0355134    -4.57   0.000    -.2319057   -.0926957
     {txt}lji_lag {c |}  {res} 1.345032   .3915708     3.43   0.001     .5775672    2.112497
{txt}high_confl~t {c |}  {res}-.7390809   .1362838    -5.42   0.000    -1.006192   -.4719697
{txt}djamne~1_lag {c |}  {res} -.114162   .1494564    -0.76   0.445    -.4070912    .1787673
 {txt}truthk1_lag {c |}  {res} .1025203   .2824254     0.36   0.717    -.4510233    .6560638
     {txt}cat_rat {c |}  {res} .0586967   .1218968     0.48   0.630    -.1802167    .2976102
    {txt}ccpr_rat {c |}  {res}-.0236458   .1545571    -0.15   0.878    -.3265723    .2792806
      {txt}africa {c |}  {res}-.1504722   .1938942    -0.78   0.438    -.5304979    .2295535
        {txt}asia {c |}  {res} -.234807    .198006    -1.19   0.236    -.6228917    .1532777
      {txt}europe {c |}  {res} .6636952   .1696019     3.91   0.000     .3312816    .9961088
{txt}tim~ll_count {c |}  {res} .0721169    .043012     1.68   0.094     -.012185    .1564188
{txt}time_kill_sq {c |}  {res}-.0173584   .0054108    -3.21   0.001    -.0279633   -.0067535
{txt}time_k~l_cub {c |}  {res} .0006439   .0001644     3.92   0.000     .0003217    .0009661
       {txt}_cons {c |}  {res} 2.682382   .7051444     3.80   0.000     1.300325     4.06444
{txt}{hline 13}{c BT}{hline 64}
({res}est4{txt} stored)

{com}. 
. eststo: probit disap_imp disap_lag  domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_disap_count time_disap_sq time_disap_cub if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-802.48316
{txt}Iteration 1:   log pseudolikelihood = {res}-586.05625
{txt}Iteration 2:   log pseudolikelihood = {res}-570.73199
{txt}Iteration 3:   log pseudolikelihood = {res}-570.02683
{txt}Iteration 4:   log pseudolikelihood = {res}-570.02446

{txt}Probit regression                                 Number of obs   = {res}      2050
                                                  {txt}Wald chi2({res}18{txt})   = {res}    308.01
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-570.02446                 {txt}Pseudo R2       = {res}    0.2897

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   disap_imp {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
   disap_lag {c |}  {res}-1.146207     .09715   -11.80   0.000    -1.336617   -.9557962
{txt}domest~1_lag {c |}  {res} .0419241   .1535165     0.27   0.785    -.2589628     .342811
{txt}domestick1.. {c |}  {res} .1566883   .1767389     0.89   0.375    -.1897137    .5030902
 {txt}polity2_lag {c |}  {res}-.0091917   .0151291    -0.61   0.543    -.0388442    .0204609
{txt}ln_gdppc_lag {c |}  {res} .0100953   .0652666     0.15   0.877    -.1178249    .1380154
{txt}ln_populat~g {c |}  {res}-.1314956   .0455493    -2.89   0.004    -.2207705   -.0422207
     {txt}lji_lag {c |}  {res} .1841541   .4509839     0.41   0.683    -.6997581    1.068066
{txt}high_confl~t {c |}  {res}-.7897831   .1682214    -4.69   0.000    -1.119491   -.4600752
{txt}djamne~1_lag {c |}  {res}-.0266664   .1424656    -0.19   0.852    -.3058937     .252561
 {txt}truthk1_lag {c |}  {res} .6429058   .2024992     3.17   0.001     .2460147    1.039797
     {txt}cat_rat {c |}  {res} .0545571   .1364306     0.40   0.689    -.2128419    .3219561
    {txt}ccpr_rat {c |}  {res}-.1582335   .1834147    -0.86   0.388    -.5177197    .2012527
      {txt}africa {c |}  {res} .2326523      .2158     1.08   0.281    -.1903079    .6556126
        {txt}asia {c |}  {res} .0132026    .227646     0.06   0.954    -.4329754    .4593805
      {txt}europe {c |}  {res}-.3524724   .4111124    -0.86   0.391    -1.158238     .453293
{txt}tim~ap_count {c |}  {res} .0179585    .040985     0.44   0.661    -.0623705    .0982876
{txt}time_di~p_sq {c |}  {res}-.0050147   .0045324    -1.11   0.269     -.013898    .0038687
{txt}time_d~p_cub {c |}  {res} .0001218   .0001169     1.04   0.297    -.0001073    .0003509
       {txt}_cons {c |}  {res} 2.426077   .8752509     2.77   0.006     .7106165    4.141537
{txt}{hline 13}{c BT}{hline 64}
({res}est5{txt} stored)

{com}. 
. 
. 
. ** table 2 in manuscript 
. eststo: mvprobit (polpris_imp=polpris_lag domestick1_lag  polity2_lag ln_gdppc_lag ln_population_lag lji_lag high_conflict time_polpris_count time_polpris_sq time_polpris_cub)  (tort_imp=tort_lag domestick1_lag  polity2_lag ln_gdppc_lag ln_population_lag lji_lag time_tort_count time_tort_sq time_tort_cub high_conflict) (kill_imp=kill_lag domestick1_lag  polity2_lag ln_gdppc_lag ln_population_lag lji_lag time_kill_count time_kill_sq time_kill_cub high_conflict) (disap_imp=disap_lag  domestick1_lag polity2_lag ln_gdppc_lag ln_population_lag lji_lag time_disap_count time_disap_sq time_disap_cub high_conflict) (domestick1_lag=polity2_lag ln_gdppc_lag  lji_lag prev_conflict_intensity time_trial_count time_trial_sq time_trial_cub)  if all_conflict_exp==1, cluster(cowcode) dr(75)

{txt}Iteration 0:{col 16}log pseudolikelihood = {res}-3153.8606{txt}  (not concave)
Iteration 1:{col 16}log pseudolikelihood = {res}-3102.2892{txt}  (not concave)
Iteration 2:{col 16}log pseudolikelihood = {res}-3100.4313{txt}  (not concave)
Iteration 3:{col 16}log pseudolikelihood = {res}-3100.2203{txt}  (not concave)
Iteration 4:{col 16}log pseudolikelihood = {res}-3100.0669{txt}  (not concave)
Iteration 5:{col 16}log pseudolikelihood = {res} -3099.976{txt}  (not concave)
Iteration 6:{col 16}log pseudolikelihood = {res}-3099.9248{txt}  (not concave)
Iteration 7:{col 16}log pseudolikelihood = {res}-3099.8717{txt}  (not concave)
Iteration 8:{col 16}log pseudolikelihood = {res}-3099.2857{txt}  
Warning: cannot do Cholesky factorization of rho matrix
Iteration 9:{col 16}log pseudolikelihood = {res}-3099.0839{txt}  
Iteration 10:{col 16}log pseudolikelihood = {res} -3097.797{txt}  
Iteration 11:{col 16}log pseudolikelihood = {res} -3097.766{txt}  
Iteration 12:{col 16}log pseudolikelihood = {res}-3097.7654{txt}  
Iteration 13:{col 16}log pseudolikelihood = {res}-3097.7654{txt}  
{res}
{txt}Multivariate probit (MSL, # draws = 75){col 51}Number of obs{col 67}= {res}      2041
{col 51}{txt}Wald chi2({res}47{txt}){col 67}= {res}   1257.21
{txt}Log pseudolikelihood = {res}-3097.7654{col 51}{txt}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 89:(Std. err. adjusted for {res:86} clusters in cowcode)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      z{col 57}   P>|z|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}polpris_imp             {txt}{c |}
{space 12}polpris_lag {c |}{col 25}{res}{space 2}-.9609628{col 37}{space 2} .0919936{col 48}{space 1}  -10.45{col 57}{space 3}0.000{col 65}{space 4}-1.141267{col 78}{space 3}-.7806587
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} 1.874504{col 37}{space 2} .6170912{col 48}{space 1}    3.04{col 57}{space 3}0.002{col 65}{space 4} .6650277{col 78}{space 3} 3.083981
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0557383{col 37}{space 2} .0114623{col 48}{space 1}    4.86{col 57}{space 3}0.000{col 65}{space 4} .0332726{col 78}{space 3}  .078204
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2}-.0617668{col 37}{space 2} .0444421{col 48}{space 1}   -1.39{col 57}{space 3}0.165{col 65}{space 4}-.1488717{col 78}{space 3}  .025338
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2}-.2334854{col 37}{space 2} .0360798{col 48}{space 1}   -6.47{col 57}{space 3}0.000{col 65}{space 4}-.3042006{col 78}{space 3}-.1627702
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} .1471582{col 37}{space 2} .3797179{col 48}{space 1}    0.39{col 57}{space 3}0.698{col 65}{space 4}-.5970751{col 78}{space 3} .8913915
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2} -.441746{col 37}{space 2} .1688869{col 48}{space 1}   -2.62{col 57}{space 3}0.009{col 65}{space 4}-.7727584{col 78}{space 3}-.1107337
{txt}{space 5}time_polpris_count {c |}{col 25}{res}{space 2}-.0279272{col 37}{space 2} .0386885{col 48}{space 1}   -0.72{col 57}{space 3}0.470{col 65}{space 4}-.1037553{col 78}{space 3}  .047901
{txt}{space 8}time_polpris_sq {c |}{col 25}{res}{space 2}-.0015309{col 37}{space 2} .0044374{col 48}{space 1}   -0.34{col 57}{space 3}0.730{col 65}{space 4}-.0102281{col 78}{space 3} .0071663
{txt}{space 7}time_polpris_cub {c |}{col 25}{res}{space 2} .0000676{col 37}{space 2} .0001191{col 48}{space 1}    0.57{col 57}{space 3}0.570{col 65}{space 4}-.0001658{col 78}{space 3} .0003011
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 3.850835{col 37}{space 2} .7144789{col 48}{space 1}    5.39{col 57}{space 3}0.000{col 65}{space 4} 2.450482{col 78}{space 3} 5.251188
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}tort_imp                {txt}{c |}
{space 15}tort_lag {c |}{col 25}{res}{space 2}-.9946766{col 37}{space 2} .1013449{col 48}{space 1}   -9.81{col 57}{space 3}0.000{col 65}{space 4}-1.193309{col 78}{space 3}-.7960443
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} .4983095{col 37}{space 2} .4388008{col 48}{space 1}    1.14{col 57}{space 3}0.256{col 65}{space 4}-.3617242{col 78}{space 3} 1.358343
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2}-.0027351{col 37}{space 2} .0120234{col 48}{space 1}   -0.23{col 57}{space 3}0.820{col 65}{space 4}-.0263006{col 78}{space 3} .0208304
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2} .0144621{col 37}{space 2} .0455402{col 48}{space 1}    0.32{col 57}{space 3}0.751{col 65}{space 4} -.074795{col 78}{space 3} .1037192
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2}-.1592517{col 37}{space 2} .0316499{col 48}{space 1}   -5.03{col 57}{space 3}0.000{col 65}{space 4}-.2212845{col 78}{space 3} -.097219
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} .8109329{col 37}{space 2} .3735601{col 48}{space 1}    2.17{col 57}{space 3}0.030{col 65}{space 4} .0787685{col 78}{space 3} 1.543097
{txt}{space 8}time_tort_count {c |}{col 25}{res}{space 2}-.0486959{col 37}{space 2}  .035318{col 48}{space 1}   -1.38{col 57}{space 3}0.168{col 65}{space 4}-.1179179{col 78}{space 3} .0205261
{txt}{space 11}time_tort_sq {c |}{col 25}{res}{space 2}-.0009244{col 37}{space 2}  .003323{col 48}{space 1}   -0.28{col 57}{space 3}0.781{col 65}{space 4}-.0074374{col 78}{space 3} .0055886
{txt}{space 10}time_tort_cub {c |}{col 25}{res}{space 2} .0000665{col 37}{space 2} .0000832{col 48}{space 1}    0.80{col 57}{space 3}0.424{col 65}{space 4}-.0000966{col 78}{space 3} .0002296
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2}-.3112613{col 37}{space 2} .1639833{col 48}{space 1}   -1.90{col 57}{space 3}0.058{col 65}{space 4}-.6326626{col 78}{space 3}   .01014
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 1.689996{col 37}{space 2} .6156716{col 48}{space 1}    2.74{col 57}{space 3}0.006{col 65}{space 4} .4833014{col 78}{space 3}  2.89669
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}kill_imp                {txt}{c |}
{space 15}kill_lag {c |}{col 25}{res}{space 2}-.8471239{col 37}{space 2}  .080279{col 48}{space 1}  -10.55{col 57}{space 3}0.000{col 65}{space 4}-1.004468{col 78}{space 3}-.6897799
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} 1.242396{col 37}{space 2} .5932402{col 48}{space 1}    2.09{col 57}{space 3}0.036{col 65}{space 4} .0796661{col 78}{space 3} 2.405125
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2}-.0390124{col 37}{space 2}  .013591{col 48}{space 1}   -2.87{col 57}{space 3}0.004{col 65}{space 4}-.0656504{col 78}{space 3}-.0123744
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2} .0139732{col 37}{space 2} .0562119{col 48}{space 1}    0.25{col 57}{space 3}0.804{col 65}{space 4}-.0962002{col 78}{space 3} .1241465
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2} -.156302{col 37}{space 2} .0319652{col 48}{space 1}   -4.89{col 57}{space 3}0.000{col 65}{space 4}-.2189526{col 78}{space 3}-.0936514
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} 1.023874{col 37}{space 2} .4620611{col 48}{space 1}    2.22{col 57}{space 3}0.027{col 65}{space 4} .1182514{col 78}{space 3} 1.929498
{txt}{space 8}time_kill_count {c |}{col 25}{res}{space 2} .0850341{col 37}{space 2} .0404306{col 48}{space 1}    2.10{col 57}{space 3}0.035{col 65}{space 4} .0057916{col 78}{space 3} .1642767
{txt}{space 11}time_kill_sq {c |}{col 25}{res}{space 2}  -.01709{col 37}{space 2} .0049158{col 48}{space 1}   -3.48{col 57}{space 3}0.001{col 65}{space 4}-.0267247{col 78}{space 3}-.0074552
{txt}{space 10}time_kill_cub {c |}{col 25}{res}{space 2} .0006161{col 37}{space 2} .0001452{col 48}{space 1}    4.24{col 57}{space 3}0.000{col 65}{space 4} .0003314{col 78}{space 3} .0009008
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2}-.7162948{col 37}{space 2} .1237446{col 48}{space 1}   -5.79{col 57}{space 3}0.000{col 65}{space 4}-.9588298{col 78}{space 3}-.4737599
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}  1.84848{col 37}{space 2} .6314846{col 48}{space 1}    2.93{col 57}{space 3}0.003{col 65}{space 4} .6107931{col 78}{space 3} 3.086167
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}disap_imp               {txt}{c |}
{space 14}disap_lag {c |}{col 25}{res}{space 2}-1.152642{col 37}{space 2} .1023901{col 48}{space 1}  -11.26{col 57}{space 3}0.000{col 65}{space 4}-1.353323{col 78}{space 3}-.9519613
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} .4761717{col 37}{space 2} .4026854{col 48}{space 1}    1.18{col 57}{space 3}0.237{col 65}{space 4}-.3130772{col 78}{space 3} 1.265421
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2}-.0163468{col 37}{space 2} .0138755{col 48}{space 1}   -1.18{col 57}{space 3}0.239{col 65}{space 4}-.0435423{col 78}{space 3} .0108487
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2}-.0646245{col 37}{space 2} .0612516{col 48}{space 1}   -1.06{col 57}{space 3}0.291{col 65}{space 4}-.1846753{col 78}{space 3} .0554264
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2}-.1388009{col 37}{space 2} .0358264{col 48}{space 1}   -3.87{col 57}{space 3}0.000{col 65}{space 4}-.2090194{col 78}{space 3}-.0685825
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} .2973846{col 37}{space 2} .5199616{col 48}{space 1}    0.57{col 57}{space 3}0.567{col 65}{space 4}-.7217214{col 78}{space 3} 1.316491
{txt}{space 7}time_disap_count {c |}{col 25}{res}{space 2} .0323148{col 37}{space 2}  .038757{col 48}{space 1}    0.83{col 57}{space 3}0.404{col 65}{space 4}-.0436475{col 78}{space 3}  .108277
{txt}{space 10}time_disap_sq {c |}{col 25}{res}{space 2}-.0064293{col 37}{space 2} .0041176{col 48}{space 1}   -1.56{col 57}{space 3}0.118{col 65}{space 4}-.0144996{col 78}{space 3}  .001641
{txt}{space 9}time_disap_cub {c |}{col 25}{res}{space 2} .0001569{col 37}{space 2} .0001056{col 48}{space 1}    1.49{col 57}{space 3}0.137{col 65}{space 4}-.0000501{col 78}{space 3}  .000364
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2}-.8052288{col 37}{space 2} .1794593{col 48}{space 1}   -4.49{col 57}{space 3}0.000{col 65}{space 4}-1.156963{col 78}{space 3} -.453495
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 3.028211{col 37}{space 2} .7223963{col 48}{space 1}    4.19{col 57}{space 3}0.000{col 65}{space 4}  1.61234{col 78}{space 3} 4.444081
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}domestick1_lag          {txt}{c |}
{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0440844{col 37}{space 2} .0164637{col 48}{space 1}    2.68{col 57}{space 3}0.007{col 65}{space 4} .0118161{col 78}{space 3} .0763526
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2} .1071799{col 37}{space 2} .0611945{col 48}{space 1}    1.75{col 57}{space 3}0.080{col 65}{space 4}-.0127592{col 78}{space 3}  .227119
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2}-1.084389{col 37}{space 2} .4732669{col 48}{space 1}   -2.29{col 57}{space 3}0.022{col 65}{space 4}-2.011975{col 78}{space 3}-.1568028
{txt}prev_conflict_intensity {c |}{col 25}{res}{space 2}-.0108955{col 37}{space 2} .1152478{col 48}{space 1}   -0.09{col 57}{space 3}0.925{col 65}{space 4} -.236777{col 78}{space 3}  .214986
{txt}{space 7}time_trial_count {c |}{col 25}{res}{space 2}-.0794719{col 37}{space 2} .0411822{col 48}{space 1}   -1.93{col 57}{space 3}0.054{col 65}{space 4}-.1601874{col 78}{space 3} .0012437
{txt}{space 10}time_trial_sq {c |}{col 25}{res}{space 2} .0051633{col 37}{space 2} .0035076{col 48}{space 1}    1.47{col 57}{space 3}0.141{col 65}{space 4}-.0017115{col 78}{space 3}  .012038
{txt}{space 9}time_trial_cub {c |}{col 25}{res}{space 2}-.0001245{col 37}{space 2} .0000829{col 48}{space 1}   -1.50{col 57}{space 3}0.133{col 65}{space 4} -.000287{col 78}{space 3}  .000038
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-1.714412{col 37}{space 2}  .425306{col 48}{space 1}   -4.03{col 57}{space 3}0.000{col 65}{space 4}-2.547997{col 78}{space 3} -.880828
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{col 1}{text}    /atrho21{col 14}{c |}{result}{space 2} .3015872{col 26}{space 2} .0653711{col 37}{space 1}    4.61{col 46}{space 3}0.000{col 55}{space 3} .1734622{col 67}{space 3} .4297121
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho31{col 14}{c |}{result}{space 2}  .294361{col 26}{space 2} .0627722{col 37}{space 1}    4.69{col 46}{space 3}0.000{col 55}{space 3} .1713298{col 67}{space 3} .4173922
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho41{col 14}{c |}{result}{space 2} .0814635{col 26}{space 2} .0750123{col 37}{space 1}    1.09{col 46}{space 3}0.277{col 55}{space 3}-.0655579{col 67}{space 3} .2284849
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho51{col 14}{c |}{result}{space 2}-.7687896{col 26}{space 2} .4186401{col 37}{space 1}   -1.84{col 46}{space 3}0.066{col 55}{space 3}-1.589309{col 67}{space 3} .0517299
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho32{col 14}{c |}{result}{space 2} .2609331{col 26}{space 2} .0592317{col 37}{space 1}    4.41{col 46}{space 3}0.000{col 55}{space 3} .1448411{col 67}{space 3} .3770252
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho42{col 14}{c |}{result}{space 2} .0670113{col 26}{space 2} .0762178{col 37}{space 1}    0.88{col 46}{space 3}0.379{col 55}{space 3}-.0823729{col 67}{space 3} .2163955
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho52{col 14}{c |}{result}{space 2}-.3281025{col 26}{space 2} .1930009{col 37}{space 1}   -1.70{col 46}{space 3}0.089{col 55}{space 3}-.7063773{col 67}{space 3} .0501723
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho43{col 14}{c |}{result}{space 2} .4830114{col 26}{space 2} .0829281{col 37}{space 1}    5.82{col 46}{space 3}0.000{col 55}{space 3} .3204753{col 67}{space 3} .6455474
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho53{col 14}{c |}{result}{space 2}-.5877601{col 26}{space 2} .3200934{col 37}{space 1}   -1.84{col 46}{space 3}0.066{col 55}{space 3}-1.215132{col 67}{space 3} .0396115
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho54{col 14}{c |}{result}{space 2}-.2095604{col 26}{space 2} .1928865{col 37}{space 1}   -1.09{col 46}{space 3}0.277{col 55}{space 3}-.5876111{col 67}{space 3} .1684903
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho21{col 14}{c |}{result}{space 2} .2927644{col 26}{space 2}  .059768{col 37}{space 1}    4.90{col 46}{space 3}0.000{col 55}{space 3} .1717432{col 67}{space 3} .4050807
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho31{col 14}{c |}{result}{space 2} .2861437{col 26}{space 2} .0576325{col 37}{space 1}    4.96{col 46}{space 3}0.000{col 55}{space 3} .1696728{col 67}{space 3} .3947313
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho41{col 14}{c |}{result}{space 2} .0812838{col 26}{space 2} .0745167{col 37}{space 1}    1.09{col 46}{space 3}0.275{col 55}{space 3}-.0654642{col 67}{space 3} .2245902
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho51{col 14}{c |}{result}{space 2}-.6462251{col 26}{space 2} .2438131{col 37}{space 1}   -2.65{col 46}{space 3}0.008{col 55}{space 3}-.9200433{col 67}{space 3} .0516838
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho32{col 14}{c |}{result}{space 2} .2551681{col 26}{space 2} .0553751{col 37}{space 1}    4.61{col 46}{space 3}0.000{col 55}{space 3} .1438366{col 67}{space 3} .3601213
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho42{col 14}{c |}{result}{space 2} .0669112{col 26}{space 2} .0758766{col 37}{space 1}    0.88{col 46}{space 3}0.378{col 55}{space 3}-.0821871{col 67}{space 3} .2130799
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho52{col 14}{c |}{result}{space 2}-.3168148{col 26}{space 2} .1736291{col 37}{space 1}   -1.82{col 46}{space 3}0.068{col 55}{space 3}-.6084001{col 67}{space 3} .0501302
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho43{col 14}{c |}{result}{space 2} .4486521{col 26}{space 2} .0662356{col 37}{space 1}    6.77{col 46}{space 3}0.000{col 55}{space 3} .3099366{col 67}{space 3} .5686649
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho53{col 14}{c |}{result}{space 2}-.5282828{col 26}{space 2} .2307609{col 37}{space 1}   -2.29{col 46}{space 3}0.022{col 55}{space 3}-.8382123{col 67}{space 3} .0395908
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho54{col 14}{c |}{result}{space 2}-.2065457{col 26}{space 2} .1846578{col 37}{space 1}   -1.12{col 46}{space 3}0.263{col 55}{space 3}-.5281753{col 67}{space 3} .1669138
{txt}{hline 13}{c BT}{hline 64}
Likelihood ratio test of  rho21 = rho31 = rho41 = rho51 = rho32 = rho42 = rho52 = rho43 = rho53 = rho54 = 0:  
             chi2({res}10{txt}) = {res}  112.19{txt}   Prob > chi2 = {res}0.0000
{txt}({res}est6{txt} stored)

{com}. esttab est6 using "table2.model1.csv", replace title(Table 4: Multivariate Probit Model) mtitles("Model 2")  obslast label se nogaps wide scalars(N ll rho2)  star(* 0.1 ** 0.05 *** 0.01) order(domestick1_lag lji_lag polity2_lag ln_gdppc_lag ln_population_lag high_conflict) 
{txt}(output written to {browse  `"table2.model1.csv"'})

{com}. 
. 
. eststo: mvprobit (polpris_imp=polpris_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe time_polpris_count time_polpris_sq time_polpris_cub)  (tort_imp=tort_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe time_tort_count time_tort_sq time_tort_cub) (kill_imp=kill_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe time_kill_count time_kill_sq time_kill_cub) (disap_imp=disap_lag  domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe time_disap_count time_disap_sq time_disap_cub) (domestick1_lag=polity2_lag ln_gdppc_lag djamnestyk1_lag truthk1_lag lji_lag prev_conflict_intensity cat_rat ccpr_rat time_trial_count time_trial_sq time_trial_cub)  if all_conflict_exp==1, cluster(cowcode) dr(75)

{txt}Iteration 0:{col 16}log pseudolikelihood = {res}-3089.2558{txt}  (not concave)
Iteration 1:{col 16}log pseudolikelihood = {res}-3039.3988{txt}  (not concave)
Iteration 2:{col 16}log pseudolikelihood = {res}-3038.3749{txt}  (not concave)
Iteration 3:{col 16}log pseudolikelihood = {res}-3036.9963{txt}  (not concave)
Iteration 4:{col 16}log pseudolikelihood = {res}-3036.8511{txt}  (not concave)
Iteration 5:{col 16}log pseudolikelihood = {res} -3036.771{txt}  (not concave)
Iteration 6:{col 16}log pseudolikelihood = {res}-3036.6925{txt}  (not concave)
Iteration 7:{col 16}log pseudolikelihood = {res}-3036.6517{txt}  (not concave)
Iteration 8:{col 16}log pseudolikelihood = {res}-3036.6307{txt}  (not concave)
Iteration 9:{col 16}log pseudolikelihood = {res}-3036.5782{txt}  (not concave)
Iteration 10:{col 16}log pseudolikelihood = {res}-3036.5248{txt}  (not concave)
Iteration 11:{col 16}log pseudolikelihood = {res}-3036.5123{txt}  (not concave)
Iteration 12:{col 16}log pseudolikelihood = {res}-3036.5006{txt}  (not concave)
Iteration 13:{col 16}log pseudolikelihood = {res}  -3036.49{txt}  (not concave)
Iteration 14:{col 16}log pseudolikelihood = {res}-3036.4795{txt}  (not concave)
Iteration 15:{col 16}log pseudolikelihood = {res}-3036.4694{txt}  (not concave)
Iteration 16:{col 16}log pseudolikelihood = {res}-3036.4597{txt}  (not concave)
Iteration 17:{col 16}log pseudolikelihood = {res}-3036.4501{txt}  (not concave)
Iteration 18:{col 16}log pseudolikelihood = {res}-3036.4408{txt}  (not concave)
Iteration 19:{col 16}log pseudolikelihood = {res}-3036.4317{txt}  (not concave)
Iteration 20:{col 16}log pseudolikelihood = {res}-3036.4229{txt}  (not concave)
Iteration 21:{col 16}log pseudolikelihood = {res}-3036.4141{txt}  (not concave)
Iteration 22:{col 16}log pseudolikelihood = {res}-3036.4056{txt}  (not concave)
Iteration 23:{col 16}log pseudolikelihood = {res}-3036.3971{txt}  (not concave)
Iteration 24:{col 16}log pseudolikelihood = {res}-3036.3888{txt}  (not concave)
Iteration 25:{col 16}log pseudolikelihood = {res}-3036.3806{txt}  (not concave)
Iteration 26:{col 16}log pseudolikelihood = {res}-3036.3725{txt}  (not concave)
Iteration 27:{col 16}log pseudolikelihood = {res}-3036.3645{txt}  (not concave)
Iteration 28:{col 16}log pseudolikelihood = {res}-3036.3565{txt}  (not concave)
Iteration 29:{col 16}log pseudolikelihood = {res}-3036.3486{txt}  (not concave)
Iteration 30:{col 16}log pseudolikelihood = {res}-3036.3407{txt}  (not concave)
Iteration 31:{col 16}log pseudolikelihood = {res}-3036.3329{txt}  (not concave)
Iteration 32:{col 16}log pseudolikelihood = {res}-3036.3251{txt}  (not concave)
Iteration 33:{col 16}log pseudolikelihood = {res}-3036.3173{txt}  (not concave)
Iteration 34:{col 16}log pseudolikelihood = {res}-3036.3095{txt}  (not concave)
Iteration 35:{col 16}log pseudolikelihood = {res}-3036.3017{txt}  (not concave)
Iteration 36:{col 16}log pseudolikelihood = {res} -3036.294{txt}  (not concave)
Iteration 37:{col 16}log pseudolikelihood = {res}-3036.2862{txt}  (not concave)
Iteration 38:{col 16}log pseudolikelihood = {res}-3036.2783{txt}  (not concave)
Iteration 39:{col 16}log pseudolikelihood = {res}-3036.2705{txt}  (not concave)
Iteration 40:{col 16}log pseudolikelihood = {res}-3036.2626{txt}  (not concave)
Iteration 41:{col 16}log pseudolikelihood = {res}-3036.2547{txt}  (not concave)
Iteration 42:{col 16}log pseudolikelihood = {res}-3036.2467{txt}  (not concave)
Iteration 43:{col 16}log pseudolikelihood = {res}-3036.2387{txt}  (not concave)
Iteration 44:{col 16}log pseudolikelihood = {res}-3036.2306{txt}  (not concave)
Iteration 45:{col 16}log pseudolikelihood = {res}-3036.2225{txt}  (not concave)
Iteration 46:{col 16}log pseudolikelihood = {res}-3036.2143{txt}  (not concave)
Iteration 47:{col 16}log pseudolikelihood = {res} -3036.206{txt}  (not concave)
Iteration 48:{col 16}log pseudolikelihood = {res}-3036.1977{txt}  (not concave)
Iteration 49:{col 16}log pseudolikelihood = {res}-3036.1893{txt}  (not concave)
Iteration 50:{col 16}log pseudolikelihood = {res}-3036.1808{txt}  (not concave)
Iteration 51:{col 16}log pseudolikelihood = {res}-3036.1722{txt}  (not concave)
Iteration 52:{col 16}log pseudolikelihood = {res}-3036.1635{txt}  (not concave)
Iteration 53:{col 16}log pseudolikelihood = {res}-3036.1548{txt}  (not concave)
Iteration 54:{col 16}log pseudolikelihood = {res} -3036.146{txt}  (not concave)
Iteration 55:{col 16}log pseudolikelihood = {res} -3036.137{txt}  (not concave)
Iteration 56:{col 16}log pseudolikelihood = {res} -3036.128{txt}  (not concave)
Iteration 57:{col 16}log pseudolikelihood = {res}-3036.1189{txt}  (not concave)
Iteration 58:{col 16}log pseudolikelihood = {res}-3036.1097{txt}  (not concave)
Iteration 59:{col 16}log pseudolikelihood = {res}-3036.1004{txt}  (not concave)
Iteration 60:{col 16}log pseudolikelihood = {res} -3036.091{txt}  (not concave)
Iteration 61:{col 16}log pseudolikelihood = {res}-3036.0814{txt}  (not concave)
Iteration 62:{col 16}log pseudolikelihood = {res}-3036.0718{txt}  (not concave)
Iteration 63:{col 16}log pseudolikelihood = {res}-3036.0621{txt}  (not concave)
Iteration 64:{col 16}log pseudolikelihood = {res}-3036.0523{txt}  (not concave)
Iteration 65:{col 16}log pseudolikelihood = {res}-3036.0424{txt}  (not concave)
Iteration 66:{col 16}log pseudolikelihood = {res}-3036.0324{txt}  (not concave)
Iteration 67:{col 16}log pseudolikelihood = {res}-3036.0224{txt}  (not concave)
Iteration 68:{col 16}log pseudolikelihood = {res}-3036.0122{txt}  (not concave)
Iteration 69:{col 16}log pseudolikelihood = {res}-3036.0019{txt}  (not concave)
Iteration 70:{col 16}log pseudolikelihood = {res}-3035.9916{txt}  (not concave)
Iteration 71:{col 16}log pseudolikelihood = {res}-3035.9811{txt}  (not concave)
Iteration 72:{col 16}log pseudolikelihood = {res}-3035.9706{txt}  (not concave)
Iteration 73:{col 16}log pseudolikelihood = {res}  -3035.96{txt}  (not concave)
Iteration 74:{col 16}log pseudolikelihood = {res}-3035.9493{txt}  (not concave)
Iteration 75:{col 16}log pseudolikelihood = {res}-3035.9386{txt}  (not concave)
Iteration 76:{col 16}log pseudolikelihood = {res}-3035.9277{txt}  (not concave)
Iteration 77:{col 16}log pseudolikelihood = {res}-3035.9169{txt}  (not concave)
Iteration 78:{col 16}log pseudolikelihood = {res}-3035.9059{txt}  (not concave)
Iteration 79:{col 16}log pseudolikelihood = {res}-3035.8949{txt}  (not concave)
Iteration 80:{col 16}log pseudolikelihood = {res}-3035.8839{txt}  (not concave)
Iteration 81:{col 16}log pseudolikelihood = {res}-3035.8728{txt}  (not concave)
Iteration 82:{col 16}log pseudolikelihood = {res}-3035.8617{txt}  (not concave)
Iteration 83:{col 16}log pseudolikelihood = {res}-3035.8506{txt}  (not concave)
Iteration 84:{col 16}log pseudolikelihood = {res}-3035.8394{txt}  (not concave)
Iteration 85:{col 16}log pseudolikelihood = {res}-3035.8282{txt}  (not concave)
Iteration 86:{col 16}log pseudolikelihood = {res} -3035.817{txt}  (not concave)
Iteration 87:{col 16}log pseudolikelihood = {res}-3035.8058{txt}  (not concave)
Iteration 88:{col 16}log pseudolikelihood = {res}-3035.7946{txt}  (not concave)
Iteration 89:{col 16}log pseudolikelihood = {res}-3035.7835{txt}  (not concave)
Iteration 90:{col 16}log pseudolikelihood = {res}-3035.7723{txt}  
Warning: cannot do Cholesky factorization of rho matrix
Warning: cannot do Cholesky factorization of rho matrix
Warning: cannot do Cholesky factorization of rho matrix
Warning: cannot do Cholesky factorization of rho matrix
Warning: cannot do Cholesky factorization of rho matrix
Warning: cannot do Cholesky factorization of rho matrix
Iteration 91:{col 16}log pseudolikelihood = {res}-3035.4174{txt}  (backed up)
Iteration 92:{col 16}log pseudolikelihood = {res}-3035.2702{txt}  
Iteration 93:{col 16}log pseudolikelihood = {res}-3035.2641{txt}  
Iteration 94:{col 16}log pseudolikelihood = {res}-3035.2641{txt}  
{res}
{txt}Multivariate probit (MSL, # draws = 75){col 51}Number of obs{col 67}= {res}      2041
{col 51}{help j_robustsingular:Wald chi2(70){col 67}= }         .
{txt}Log pseudolikelihood = {res}-3035.2641{col 51}{txt}Prob > chi2{col 67}= {res}         .

{txt}{ralign 89:(Std. err. adjusted for {res:86} clusters in cowcode)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      z{col 57}   P>|z|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}polpris_imp             {txt}{c |}
{space 12}polpris_lag {c |}{col 25}{res}{space 2}-1.017004{col 37}{space 2} .0907113{col 48}{space 1}  -11.21{col 57}{space 3}0.000{col 65}{space 4}-1.194794{col 78}{space 3}-.8392129
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} 1.693705{col 37}{space 2} .7662293{col 48}{space 1}    2.21{col 57}{space 3}0.027{col 65}{space 4} .1919231{col 78}{space 3} 3.195487
{txt}{space 2}domestick1_lag_two_yr {c |}{col 25}{res}{space 2}-.3434151{col 37}{space 2} .2146734{col 48}{space 1}   -1.60{col 57}{space 3}0.110{col 65}{space 4}-.7641672{col 78}{space 3} .0773369
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0558683{col 37}{space 2} .0133951{col 48}{space 1}    4.17{col 57}{space 3}0.000{col 65}{space 4} .0296144{col 78}{space 3} .0821223
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2}-.0895059{col 37}{space 2} .0615717{col 48}{space 1}   -1.45{col 57}{space 3}0.146{col 65}{space 4}-.2101842{col 78}{space 3} .0311724
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2}-.1987204{col 37}{space 2} .0360535{col 48}{space 1}   -5.51{col 57}{space 3}0.000{col 65}{space 4} -.269384{col 78}{space 3}-.1280569
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} .2272862{col 37}{space 2}  .365067{col 48}{space 1}    0.62{col 57}{space 3}0.534{col 65}{space 4} -.488232{col 78}{space 3} .9428045
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2}-.4913497{col 37}{space 2} .1714728{col 48}{space 1}   -2.87{col 57}{space 3}0.004{col 65}{space 4}-.8274302{col 78}{space 3}-.1552691
{txt}{space 8}djamnestyk1_lag {c |}{col 25}{res}{space 2} .0272097{col 37}{space 2} .1357453{col 48}{space 1}    0.20{col 57}{space 3}0.841{col 65}{space 4}-.2388463{col 78}{space 3} .2932656
{txt}{space 12}truthk1_lag {c |}{col 25}{res}{space 2} .2032423{col 37}{space 2} .3413346{col 48}{space 1}    0.60{col 57}{space 3}0.552{col 65}{space 4}-.4657613{col 78}{space 3} .8722459
{txt}{space 16}cat_rat {c |}{col 25}{res}{space 2}-.0260529{col 37}{space 2} .1093373{col 48}{space 1}   -0.24{col 57}{space 3}0.812{col 65}{space 4}-.2403501{col 78}{space 3} .1882444
{txt}{space 15}ccpr_rat {c |}{col 25}{res}{space 2}-.2711472{col 37}{space 2}  .132573{col 48}{space 1}   -2.05{col 57}{space 3}0.041{col 65}{space 4}-.5309856{col 78}{space 3}-.0113089
{txt}{space 17}africa {c |}{col 25}{res}{space 2}-.1066717{col 37}{space 2} .1609276{col 48}{space 1}   -0.66{col 57}{space 3}0.507{col 65}{space 4}-.4220841{col 78}{space 3} .2087406
{txt}{space 19}asia {c |}{col 25}{res}{space 2}-.4150233{col 37}{space 2} .1468824{col 48}{space 1}   -2.83{col 57}{space 3}0.005{col 65}{space 4}-.7029076{col 78}{space 3}-.1271391
{txt}{space 17}europe {c |}{col 25}{res}{space 2} .1871155{col 37}{space 2} .2184611{col 48}{space 1}    0.86{col 57}{space 3}0.392{col 65}{space 4}-.2410605{col 78}{space 3} .6152915
{txt}{space 5}time_polpris_count {c |}{col 25}{res}{space 2}-.0370217{col 37}{space 2} .0404452{col 48}{space 1}   -0.92{col 57}{space 3}0.360{col 65}{space 4}-.1162929{col 78}{space 3} .0422494
{txt}{space 8}time_polpris_sq {c |}{col 25}{res}{space 2}-.0004797{col 37}{space 2} .0046851{col 48}{space 1}   -0.10{col 57}{space 3}0.918{col 65}{space 4}-.0096625{col 78}{space 3}  .008703
{txt}{space 7}time_polpris_cub {c |}{col 25}{res}{space 2} .0000483{col 37}{space 2} .0001253{col 48}{space 1}    0.39{col 57}{space 3}0.700{col 65}{space 4}-.0001973{col 78}{space 3} .0002939
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 3.862636{col 37}{space 2} .7614206{col 48}{space 1}    5.07{col 57}{space 3}0.000{col 65}{space 4} 2.370279{col 78}{space 3} 5.354993
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}tort_imp                {txt}{c |}
{space 15}tort_lag {c |}{col 25}{res}{space 2}-1.101032{col 37}{space 2} .0951267{col 48}{space 1}  -11.57{col 57}{space 3}0.000{col 65}{space 4}-1.287477{col 78}{space 3}-.9145873
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} .1202888{col 37}{space 2} .4361684{col 48}{space 1}    0.28{col 57}{space 3}0.783{col 65}{space 4}-.7345855{col 78}{space 3} .9751632
{txt}{space 2}domestick1_lag_two_yr {c |}{col 25}{res}{space 2}-.3761813{col 37}{space 2} .1683574{col 48}{space 1}   -2.23{col 57}{space 3}0.025{col 65}{space 4}-.7061557{col 78}{space 3}-.0462069
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0071066{col 37}{space 2} .0141512{col 48}{space 1}    0.50{col 57}{space 3}0.616{col 65}{space 4}-.0206293{col 78}{space 3} .0348424
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2}  .019312{col 37}{space 2} .0580708{col 48}{space 1}    0.33{col 57}{space 3}0.739{col 65}{space 4}-.0945046{col 78}{space 3} .1331286
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2}-.1515364{col 37}{space 2} .0367806{col 48}{space 1}   -4.12{col 57}{space 3}0.000{col 65}{space 4}-.2236249{col 78}{space 3}-.0794478
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} .6903346{col 37}{space 2}  .354584{col 48}{space 1}    1.95{col 57}{space 3}0.052{col 65}{space 4}-.0046371{col 78}{space 3} 1.385306
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2}-.3865238{col 37}{space 2} .1709908{col 48}{space 1}   -2.26{col 57}{space 3}0.024{col 65}{space 4}-.7216595{col 78}{space 3}-.0513881
{txt}{space 8}djamnestyk1_lag {c |}{col 25}{res}{space 2}  .015375{col 37}{space 2} .1431183{col 48}{space 1}    0.11{col 57}{space 3}0.914{col 65}{space 4}-.2651318{col 78}{space 3} .2958817
{txt}{space 12}truthk1_lag {c |}{col 25}{res}{space 2} .6607442{col 37}{space 2} .2791469{col 48}{space 1}    2.37{col 57}{space 3}0.018{col 65}{space 4} .1136264{col 78}{space 3} 1.207862
{txt}{space 16}cat_rat {c |}{col 25}{res}{space 2}-.2982161{col 37}{space 2} .1028094{col 48}{space 1}   -2.90{col 57}{space 3}0.004{col 65}{space 4}-.4997189{col 78}{space 3}-.0967133
{txt}{space 15}ccpr_rat {c |}{col 25}{res}{space 2}-.2426912{col 37}{space 2} .1142609{col 48}{space 1}   -2.12{col 57}{space 3}0.034{col 65}{space 4}-.4666384{col 78}{space 3}-.0187441
{txt}{space 17}africa {c |}{col 25}{res}{space 2} .1108715{col 37}{space 2} .1492676{col 48}{space 1}    0.74{col 57}{space 3}0.458{col 65}{space 4}-.1816876{col 78}{space 3} .4034306
{txt}{space 19}asia {c |}{col 25}{res}{space 2}-.1568046{col 37}{space 2} .1623731{col 48}{space 1}   -0.97{col 57}{space 3}0.334{col 65}{space 4}-.4750501{col 78}{space 3} .1614409
{txt}{space 17}europe {c |}{col 25}{res}{space 2} .4894622{col 37}{space 2} .1629999{col 48}{space 1}    3.00{col 57}{space 3}0.003{col 65}{space 4} .1699882{col 78}{space 3} .8089362
{txt}{space 8}time_tort_count {c |}{col 25}{res}{space 2}-.0454174{col 37}{space 2} .0371258{col 48}{space 1}   -1.22{col 57}{space 3}0.221{col 65}{space 4}-.1181826{col 78}{space 3} .0273478
{txt}{space 11}time_tort_sq {c |}{col 25}{res}{space 2}-.0004781{col 37}{space 2} .0035174{col 48}{space 1}   -0.14{col 57}{space 3}0.892{col 65}{space 4} -.007372{col 78}{space 3} .0064159
{txt}{space 10}time_tort_cub {c |}{col 25}{res}{space 2} .0000491{col 37}{space 2} .0000904{col 48}{space 1}    0.54{col 57}{space 3}0.587{col 65}{space 4}-.0001281{col 78}{space 3} .0002263
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 1.911122{col 37}{space 2} .7171586{col 48}{space 1}    2.66{col 57}{space 3}0.008{col 65}{space 4} .5055166{col 78}{space 3} 3.316727
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}kill_imp                {txt}{c |}
{space 15}kill_lag {c |}{col 25}{res}{space 2}-.9622363{col 37}{space 2} .0858612{col 48}{space 1}  -11.21{col 57}{space 3}0.000{col 65}{space 4}-1.130521{col 78}{space 3}-.7939515
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} 1.412047{col 37}{space 2} 1.093658{col 48}{space 1}    1.29{col 57}{space 3}0.197{col 65}{space 4}-.7314822{col 78}{space 3} 3.555577
{txt}{space 2}domestick1_lag_two_yr {c |}{col 25}{res}{space 2}-.0986376{col 37}{space 2}  .168609{col 48}{space 1}   -0.59{col 57}{space 3}0.559{col 65}{space 4}-.4291051{col 78}{space 3}   .23183
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2}-.0545969{col 37}{space 2} .0146449{col 48}{space 1}   -3.73{col 57}{space 3}0.000{col 65}{space 4}-.0833004{col 78}{space 3}-.0258934
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2} -.069421{col 37}{space 2} .0616544{col 48}{space 1}   -1.13{col 57}{space 3}0.260{col 65}{space 4}-.1902613{col 78}{space 3} .0514194
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2}-.1645095{col 37}{space 2} .0342493{col 48}{space 1}   -4.80{col 57}{space 3}0.000{col 65}{space 4}-.2316368{col 78}{space 3}-.0973822
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} 1.365066{col 37}{space 2} .3953567{col 48}{space 1}    3.45{col 57}{space 3}0.001{col 65}{space 4} .5901808{col 78}{space 3}  2.13995
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2}-.7792405{col 37}{space 2} .1353628{col 48}{space 1}   -5.76{col 57}{space 3}0.000{col 65}{space 4}-1.044547{col 78}{space 3}-.5139342
{txt}{space 8}djamnestyk1_lag {c |}{col 25}{res}{space 2}  -.19954{col 37}{space 2} .1570568{col 48}{space 1}   -1.27{col 57}{space 3}0.204{col 65}{space 4}-.5073656{col 78}{space 3} .1082857
{txt}{space 12}truthk1_lag {c |}{col 25}{res}{space 2}-.1111941{col 37}{space 2} .3100852{col 48}{space 1}   -0.36{col 57}{space 3}0.720{col 65}{space 4}  -.71895{col 78}{space 3} .4965618
{txt}{space 16}cat_rat {c |}{col 25}{res}{space 2} .0537451{col 37}{space 2} .1244482{col 48}{space 1}    0.43{col 57}{space 3}0.666{col 65}{space 4}-.1901689{col 78}{space 3} .2976592
{txt}{space 15}ccpr_rat {c |}{col 25}{res}{space 2}-.0207976{col 37}{space 2} .1617231{col 48}{space 1}   -0.13{col 57}{space 3}0.898{col 65}{space 4} -.337769{col 78}{space 3} .2961738
{txt}{space 17}africa {c |}{col 25}{res}{space 2}-.1282706{col 37}{space 2} .1911868{col 48}{space 1}   -0.67{col 57}{space 3}0.502{col 65}{space 4}-.5029899{col 78}{space 3} .2464487
{txt}{space 19}asia {c |}{col 25}{res}{space 2}-.2150748{col 37}{space 2} .1935392{col 48}{space 1}   -1.11{col 57}{space 3}0.266{col 65}{space 4}-.5944046{col 78}{space 3}  .164255
{txt}{space 17}europe {c |}{col 25}{res}{space 2} .6178208{col 37}{space 2} .1811059{col 48}{space 1}    3.41{col 57}{space 3}0.001{col 65}{space 4} .2628597{col 78}{space 3} .9727819
{txt}{space 8}time_kill_count {c |}{col 25}{res}{space 2} .0722607{col 37}{space 2} .0413174{col 48}{space 1}    1.75{col 57}{space 3}0.080{col 65}{space 4}  -.00872{col 78}{space 3} .1532414
{txt}{space 11}time_kill_sq {c |}{col 25}{res}{space 2}-.0160711{col 37}{space 2} .0051533{col 48}{space 1}   -3.12{col 57}{space 3}0.002{col 65}{space 4}-.0261714{col 78}{space 3}-.0059708
{txt}{space 10}time_kill_cub {c |}{col 25}{res}{space 2} .0005894{col 37}{space 2} .0001537{col 48}{space 1}    3.84{col 57}{space 3}0.000{col 65}{space 4} .0002882{col 78}{space 3} .0008905
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.649778{col 37}{space 2} .7026983{col 48}{space 1}    3.77{col 57}{space 3}0.000{col 65}{space 4} 1.272515{col 78}{space 3} 4.027041
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}disap_imp               {txt}{c |}
{space 14}disap_lag {c |}{col 25}{res}{space 2} -1.19734{col 37}{space 2}   .09106{col 48}{space 1}  -13.15{col 57}{space 3}0.000{col 65}{space 4}-1.375815{col 78}{space 3}-1.018866
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2}  .453669{col 37}{space 2} .5450488{col 48}{space 1}    0.83{col 57}{space 3}0.405{col 65}{space 4} -.614607{col 78}{space 3} 1.521945
{txt}{space 2}domestick1_lag_two_yr {c |}{col 25}{res}{space 2}  .098541{col 37}{space 2} .1926708{col 48}{space 1}    0.51{col 57}{space 3}0.609{col 65}{space 4}-.2790869{col 78}{space 3} .4761688
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2}-.0091151{col 37}{space 2} .0146081{col 48}{space 1}   -0.62{col 57}{space 3}0.533{col 65}{space 4}-.0377464{col 78}{space 3} .0195161
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2}  .020031{col 37}{space 2} .0633992{col 48}{space 1}    0.32{col 57}{space 3}0.752{col 65}{space 4}-.1042291{col 78}{space 3}  .144291
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2}-.1356673{col 37}{space 2} .0434587{col 48}{space 1}   -3.12{col 57}{space 3}0.002{col 65}{space 4}-.2208447{col 78}{space 3}-.0504899
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} .1714837{col 37}{space 2} .4546745{col 48}{space 1}    0.38{col 57}{space 3}0.706{col 65}{space 4} -.719662{col 78}{space 3} 1.062629
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2}-.8590733{col 37}{space 2} .1771302{col 48}{space 1}   -4.85{col 57}{space 3}0.000{col 65}{space 4}-1.206242{col 78}{space 3}-.5119045
{txt}{space 8}djamnestyk1_lag {c |}{col 25}{res}{space 2}-.0286407{col 37}{space 2}  .138576{col 48}{space 1}   -0.21{col 57}{space 3}0.836{col 65}{space 4}-.3002447{col 78}{space 3} .2429633
{txt}{space 12}truthk1_lag {c |}{col 25}{res}{space 2} .5616653{col 37}{space 2} .2352251{col 48}{space 1}    2.39{col 57}{space 3}0.017{col 65}{space 4} .1006325{col 78}{space 3} 1.022698
{txt}{space 16}cat_rat {c |}{col 25}{res}{space 2} .0494948{col 37}{space 2} .1382347{col 48}{space 1}    0.36{col 57}{space 3}0.720{col 65}{space 4}-.2214402{col 78}{space 3} .3204298
{txt}{space 15}ccpr_rat {c |}{col 25}{res}{space 2}-.1843758{col 37}{space 2} .1870063{col 48}{space 1}   -0.99{col 57}{space 3}0.324{col 65}{space 4}-.5509013{col 78}{space 3} .1821498
{txt}{space 17}africa {c |}{col 25}{res}{space 2}  .238285{col 37}{space 2} .2070491{col 48}{space 1}    1.15{col 57}{space 3}0.250{col 65}{space 4}-.1675238{col 78}{space 3} .6440938
{txt}{space 19}asia {c |}{col 25}{res}{space 2}  .019779{col 37}{space 2} .2213273{col 48}{space 1}    0.09{col 57}{space 3}0.929{col 65}{space 4}-.4140146{col 78}{space 3} .4535726
{txt}{space 17}europe {c |}{col 25}{res}{space 2}-.3885668{col 37}{space 2} .4202878{col 48}{space 1}   -0.92{col 57}{space 3}0.355{col 65}{space 4}-1.212316{col 78}{space 3}  .435182
{txt}{space 7}time_disap_count {c |}{col 25}{res}{space 2}  .030863{col 37}{space 2} .0374794{col 48}{space 1}    0.82{col 57}{space 3}0.410{col 65}{space 4}-.0425953{col 78}{space 3} .1043212
{txt}{space 10}time_disap_sq {c |}{col 25}{res}{space 2} -.006038{col 37}{space 2} .0040878{col 48}{space 1}   -1.48{col 57}{space 3}0.140{col 65}{space 4}  -.01405{col 78}{space 3}  .001974
{txt}{space 9}time_disap_cub {c |}{col 25}{res}{space 2} .0001462{col 37}{space 2} .0001069{col 48}{space 1}    1.37{col 57}{space 3}0.171{col 65}{space 4}-.0000633{col 78}{space 3} .0003557
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.500175{col 37}{space 2} .8649017{col 48}{space 1}    2.89{col 57}{space 3}0.004{col 65}{space 4} .8049987{col 78}{space 3} 4.195351
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}domestick1_lag          {txt}{c |}
{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0374815{col 37}{space 2} .0178264{col 48}{space 1}    2.10{col 57}{space 3}0.036{col 65}{space 4} .0025424{col 78}{space 3} .0724206
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2} .1030034{col 37}{space 2} .0649313{col 48}{space 1}    1.59{col 57}{space 3}0.113{col 65}{space 4}-.0242597{col 78}{space 3} .2302665
{txt}{space 8}djamnestyk1_lag {c |}{col 25}{res}{space 2}  .208626{col 37}{space 2} .1732398{col 48}{space 1}    1.20{col 57}{space 3}0.228{col 65}{space 4}-.1309177{col 78}{space 3} .5481697
{txt}{space 12}truthk1_lag {c |}{col 25}{res}{space 2} .6175196{col 37}{space 2} .3786832{col 48}{space 1}    1.63{col 57}{space 3}0.103{col 65}{space 4}-.1246859{col 78}{space 3} 1.359725
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2}-.9643417{col 37}{space 2} .4791331{col 48}{space 1}   -2.01{col 57}{space 3}0.044{col 65}{space 4}-1.903425{col 78}{space 3} -.025258
{txt}prev_conflict_intensity {c |}{col 25}{res}{space 2}-.0383649{col 37}{space 2} .1189569{col 48}{space 1}   -0.32{col 57}{space 3}0.747{col 65}{space 4}-.2715161{col 78}{space 3} .1947862
{txt}{space 16}cat_rat {c |}{col 25}{res}{space 2} .0686608{col 37}{space 2} .1564013{col 48}{space 1}    0.44{col 57}{space 3}0.661{col 65}{space 4}-.2378801{col 78}{space 3} .3752016
{txt}{space 15}ccpr_rat {c |}{col 25}{res}{space 2}-.0000202{col 37}{space 2} .1955306{col 48}{space 1}   -0.00{col 57}{space 3}1.000{col 65}{space 4}-.3832531{col 78}{space 3} .3832128
{txt}{space 7}time_trial_count {c |}{col 25}{res}{space 2}-.0815033{col 37}{space 2} .0431875{col 48}{space 1}   -1.89{col 57}{space 3}0.059{col 65}{space 4}-.1661493{col 78}{space 3} .0031427
{txt}{space 10}time_trial_sq {c |}{col 25}{res}{space 2} .0053965{col 37}{space 2} .0036314{col 48}{space 1}    1.49{col 57}{space 3}0.137{col 65}{space 4} -.001721{col 78}{space 3} .0125139
{txt}{space 9}time_trial_cub {c |}{col 25}{res}{space 2} -.000129{col 37}{space 2} .0000859{col 48}{space 1}   -1.50{col 57}{space 3}0.133{col 65}{space 4}-.0002973{col 78}{space 3} .0000393
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-1.766104{col 37}{space 2} .4303403{col 48}{space 1}   -4.10{col 57}{space 3}0.000{col 65}{space 4}-2.609555{col 78}{space 3}-.9226522
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{col 1}{text}    /atrho21{col 14}{c |}{result}{space 2} .2689533{col 26}{space 2}  .063582{col 37}{space 1}    4.23{col 46}{space 3}0.000{col 55}{space 3} .1443349{col 67}{space 3} .3935717
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho31{col 14}{c |}{result}{space 2} .2878139{col 26}{space 2} .0651215{col 37}{space 1}    4.42{col 46}{space 3}0.000{col 55}{space 3} .1601782{col 67}{space 3} .4154496
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho41{col 14}{c |}{result}{space 2} .0728796{col 26}{space 2} .0659928{col 37}{space 1}    1.10{col 46}{space 3}0.269{col 55}{space 3} -.056464{col 67}{space 3} .2022232
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho51{col 14}{c |}{result}{space 2}-.6574534{col 26}{space 2} .4488337{col 37}{space 1}   -1.46{col 46}{space 3}0.143{col 55}{space 3}-1.537151{col 67}{space 3} .2222444
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho32{col 14}{c |}{result}{space 2} .2659598{col 26}{space 2} .0595208{col 37}{space 1}    4.47{col 46}{space 3}0.000{col 55}{space 3} .1493012{col 67}{space 3} .3826184
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho42{col 14}{c |}{result}{space 2} .0716212{col 26}{space 2} .0755021{col 37}{space 1}    0.95{col 46}{space 3}0.343{col 55}{space 3}-.0763602{col 67}{space 3} .2196026
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho52{col 14}{c |}{result}{space 2}-.1784798{col 26}{space 2} .1889093{col 37}{space 1}   -0.94{col 46}{space 3}0.345{col 55}{space 3}-.5487353{col 67}{space 3} .1917757
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho43{col 14}{c |}{result}{space 2}  .516036{col 26}{space 2} .0744309{col 37}{space 1}    6.93{col 46}{space 3}0.000{col 55}{space 3} .3701542{col 67}{space 3} .6619178
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho53{col 14}{c |}{result}{space 2}-.7077098{col 26}{space 2} .6703691{col 37}{space 1}   -1.06{col 46}{space 3}0.291{col 55}{space 3}-2.021609{col 67}{space 3} .6061896
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho54{col 14}{c |}{result}{space 2}-.2029884{col 26}{space 2} .2569255{col 37}{space 1}   -0.79{col 46}{space 3}0.429{col 55}{space 3}-.7065531{col 67}{space 3} .3005762
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho21{col 14}{c |}{result}{space 2} .2626506{col 26}{space 2} .0591957{col 37}{space 1}    4.44{col 46}{space 3}0.000{col 55}{space 3} .1433409{col 67}{space 3} .3744352
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho31{col 14}{c |}{result}{space 2} .2801215{col 26}{space 2} .0600115{col 37}{space 1}    4.67{col 46}{space 3}0.000{col 55}{space 3} .1588222{col 67}{space 3} .3930901
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho41{col 14}{c |}{result}{space 2} .0727508{col 26}{space 2} .0656435{col 37}{space 1}    1.11{col 46}{space 3}0.268{col 55}{space 3} -.056404{col 67}{space 3} .1995109
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho51{col 14}{c |}{result}{space 2}-.5766662{col 26}{space 2} .2995768{col 37}{space 1}   -1.92{col 46}{space 3}0.054{col 55}{space 3}-.9116404{col 67}{space 3} .2186562
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho32{col 14}{c |}{result}{space 2} .2598615{col 26}{space 2} .0555015{col 37}{space 1}    4.68{col 46}{space 3}0.000{col 55}{space 3} .1482017{col 67}{space 3} .3649792
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho42{col 14}{c |}{result}{space 2}  .071499{col 26}{space 2} .0751161{col 37}{space 1}    0.95{col 46}{space 3}0.341{col 55}{space 3}-.0762121{col 67}{space 3} .2161392
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho52{col 14}{c |}{result}{space 2}-.1766085{col 26}{space 2} .1830172{col 37}{space 1}   -0.96{col 46}{space 3}0.335{col 55}{space 3}-.4995718{col 67}{space 3} .1894587
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho43{col 14}{c |}{result}{space 2} .4746348{col 26}{space 2} .0576632{col 37}{space 1}    8.23{col 46}{space 3}0.000{col 55}{space 3} .3541266{col 67}{space 3} .5796383
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho53{col 14}{c |}{result}{space 2}-.6092387{col 26}{space 2}  .421547{col 37}{space 1}   -1.45{col 46}{space 3}0.148{col 55}{space 3}-.9655229{col 67}{space 3} .5414393
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho54{col 14}{c |}{result}{space 2}-.2002456{col 26}{space 2} .2466232{col 37}{space 1}   -0.81{col 46}{space 3}0.417{col 55}{space 3}-.6085108{col 67}{space 3} .2918398
{txt}{hline 13}{c BT}{hline 64}
Likelihood ratio test of  rho21 = rho31 = rho41 = rho51 = rho32 = rho42 = rho52 = rho43 = rho53 = rho54 = 0:  
             chi2({res}10{txt}) = {res} 107.983{txt}   Prob > chi2 = {res}0.0000
{txt}({res}est7{txt} stored)

{com}. 
. ***models with v-dem dvars*** - table A1 -
. 
. eststo: mvprobit (v2smarrest_ord_imp=v2smarrest_ord_lag domestick1_lag  polity2_lag ln_gdppc_lag ln_population_lag lji_lag high_conflict  )  (vdem_tort_imp=v2cltort_ord_lag domestick1_lag  polity2_lag ln_gdppc_lag ln_population_lag lji_lag high_conflict ) (v2clkill_ord_imp=v2clkill_ord_lag  domestick1_lag  polity2_lag ln_gdppc_lag ln_population_lag lji_lag high_conflict ) (domestick1_lag=polity2_lag ln_gdppc_lag lji_lag prev_conflict_intensity) if all_conflict_exp==1, cluster(cowcode) dr(31)

{txt}Iteration 0:{col 16}log pseudolikelihood = {res}-507.77175{txt}  (not concave)
Iteration 1:{col 16}log pseudolikelihood = {res}-486.05664{txt}  (not concave)
Iteration 2:{col 16}log pseudolikelihood = {res}-483.79178{txt}  (not concave)
Iteration 3:{col 16}log pseudolikelihood = {res}-483.35047{txt}  
Iteration 4:{col 16}log pseudolikelihood = {res}-482.86622{txt}  (not concave)
Iteration 5:{col 16}log pseudolikelihood = {res}-482.83107{txt}  (not concave)
Iteration 6:{col 16}log pseudolikelihood = {res}-482.81603{txt}  (not concave)
Iteration 7:{col 16}log pseudolikelihood = {res}    -482.8{txt}  (not concave)
Iteration 8:{col 16}log pseudolikelihood = {res}-482.78881{txt}  (not concave)
Iteration 9:{col 16}log pseudolikelihood = {res}-482.77803{txt}  (not concave)
Iteration 10:{col 16}log pseudolikelihood = {res}-482.76028{txt}  (not concave)
Iteration 11:{col 16}log pseudolikelihood = {res}-482.74365{txt}  (not concave)
Iteration 12:{col 16}log pseudolikelihood = {res}-482.61488{txt}  
Iteration 13:{col 16}log pseudolikelihood = {res} -482.5638{txt}  
Iteration 14:{col 16}log pseudolikelihood = {res}-482.56348{txt}  
Iteration 15:{col 16}log pseudolikelihood = {res}-482.56348{txt}  
{res}
{txt}Multivariate probit (MSL, # draws = 31){col 51}Number of obs{col 67}= {res}      1007
{col 51}{txt}Wald chi2({res}25{txt}){col 67}= {res}    218.08
{txt}Log pseudolikelihood = {res}-482.56348{col 51}{txt}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 89:(Std. err. adjusted for {res:86} clusters in cowcode)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      z{col 57}   P>|z|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}v2smarrest_ord_imp      {txt}{c |}
{space 5}v2smarrest_ord_lag {c |}{col 25}{res}{space 2}-.5695259{col 37}{space 2} .1443371{col 48}{space 1}   -3.95{col 57}{space 3}0.000{col 65}{space 4}-.8524213{col 78}{space 3}-.2866305
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} 1.243072{col 37}{space 2} .6005454{col 48}{space 1}    2.07{col 57}{space 3}0.038{col 65}{space 4} .0660246{col 78}{space 3} 2.420119
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0961157{col 37}{space 2} .0329894{col 48}{space 1}    2.91{col 57}{space 3}0.004{col 65}{space 4} .0314576{col 78}{space 3} .1607738
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2} .0266724{col 37}{space 2} .0916471{col 48}{space 1}    0.29{col 57}{space 3}0.771{col 65}{space 4}-.1529527{col 78}{space 3} .2062975
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2}-.0011894{col 37}{space 2} .0977244{col 48}{space 1}   -0.01{col 57}{space 3}0.990{col 65}{space 4}-.1927257{col 78}{space 3} .1903469
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2}-1.876375{col 37}{space 2} .8057243{col 48}{space 1}   -2.33{col 57}{space 3}0.020{col 65}{space 4}-3.455565{col 78}{space 3}-.2971842
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2}-1.871619{col 37}{space 2} 1.199774{col 48}{space 1}   -1.56{col 57}{space 3}0.119{col 65}{space 4}-4.223132{col 78}{space 3} .4798941
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} -1.27801{col 37}{space 2} 1.617515{col 48}{space 1}   -0.79{col 57}{space 3}0.429{col 65}{space 4} -4.44828{col 78}{space 3} 1.892261
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}vdem_tort_imp           {txt}{c |}
{space 7}v2cltort_ord_lag {c |}{col 25}{res}{space 2}-.7406669{col 37}{space 2} .1295103{col 48}{space 1}   -5.72{col 57}{space 3}0.000{col 65}{space 4}-.9945025{col 78}{space 3}-.4868313
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} 2.189348{col 37}{space 2} .5237879{col 48}{space 1}    4.18{col 57}{space 3}0.000{col 65}{space 4} 1.162743{col 78}{space 3} 3.215954
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0739938{col 37}{space 2} .0324858{col 48}{space 1}    2.28{col 57}{space 3}0.023{col 65}{space 4} .0103229{col 78}{space 3} .1376647
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2}-.0167162{col 37}{space 2} .1005307{col 48}{space 1}   -0.17{col 57}{space 3}0.868{col 65}{space 4}-.2137527{col 78}{space 3} .1803204
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2}-.2004895{col 37}{space 2} .0646574{col 48}{space 1}   -3.10{col 57}{space 3}0.002{col 65}{space 4}-.3272157{col 78}{space 3}-.0737634
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} .5193901{col 37}{space 2} .8856895{col 48}{space 1}    0.59{col 57}{space 3}0.558{col 65}{space 4}-1.216529{col 78}{space 3}  2.25531
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2} .0493439{col 37}{space 2} .2899627{col 48}{space 1}    0.17{col 57}{space 3}0.865{col 65}{space 4}-.5189725{col 78}{space 3} .6176603
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}  2.39684{col 37}{space 2} 1.308371{col 48}{space 1}    1.83{col 57}{space 3}0.067{col 65}{space 4}  -.16752{col 78}{space 3} 4.961199
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}v2clkill_ord_imp        {txt}{c |}
{space 7}v2clkill_ord_lag {c |}{col 25}{res}{space 2}-.4290665{col 37}{space 2} .1027263{col 48}{space 1}   -4.18{col 57}{space 3}0.000{col 65}{space 4}-.6304062{col 78}{space 3}-.2277267
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} .6177824{col 37}{space 2} .5739249{col 48}{space 1}    1.08{col 57}{space 3}0.282{col 65}{space 4}-.5070899{col 78}{space 3} 1.742655
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0525902{col 37}{space 2} .0245017{col 48}{space 1}    2.15{col 57}{space 3}0.032{col 65}{space 4} .0045677{col 78}{space 3} .1006127
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2} .0508871{col 37}{space 2} .0927325{col 48}{space 1}    0.55{col 57}{space 3}0.583{col 65}{space 4}-.1308653{col 78}{space 3} .2326395
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2} -.067017{col 37}{space 2} .0640329{col 48}{space 1}   -1.05{col 57}{space 3}0.295{col 65}{space 4}-.1925191{col 78}{space 3} .0584851
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2}-1.114337{col 37}{space 2} .6116239{col 48}{space 1}   -1.82{col 57}{space 3}0.068{col 65}{space 4}-2.313098{col 78}{space 3} .0844237
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2}-.0908289{col 37}{space 2} .3119736{col 48}{space 1}   -0.29{col 57}{space 3}0.771{col 65}{space 4} -.702286{col 78}{space 3} .5206282
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .1970493{col 37}{space 2} 1.151985{col 48}{space 1}    0.17{col 57}{space 3}0.864{col 65}{space 4}  -2.0608{col 78}{space 3} 2.454899
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}domestick1_lag          {txt}{c |}
{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0432464{col 37}{space 2} .0283185{col 48}{space 1}    1.53{col 57}{space 3}0.127{col 65}{space 4}-.0122568{col 78}{space 3} .0987496
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2} .1165474{col 37}{space 2} .0893376{col 48}{space 1}    1.30{col 57}{space 3}0.192{col 65}{space 4}-.0585511{col 78}{space 3} .2916459
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} -.853885{col 37}{space 2} .7656718{col 48}{space 1}   -1.12{col 57}{space 3}0.265{col 65}{space 4}-2.354574{col 78}{space 3} .6468042
{txt}prev_conflict_intensity {c |}{col 25}{res}{space 2}   .25075{col 37}{space 2} .1830132{col 48}{space 1}    1.37{col 57}{space 3}0.171{col 65}{space 4}-.1079493{col 78}{space 3} .6094493
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-2.694946{col 37}{space 2} .5340486{col 48}{space 1}   -5.05{col 57}{space 3}0.000{col 65}{space 4}-3.741662{col 78}{space 3} -1.64823
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{col 1}{text}    /atrho21{col 14}{c |}{result}{space 2} .7310812{col 26}{space 2} .1769956{col 37}{space 1}    4.13{col 46}{space 3}0.000{col 55}{space 3} .3841763{col 67}{space 3} 1.077986
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho31{col 14}{c |}{result}{space 2} .7426677{col 26}{space 2} .2287122{col 37}{space 1}    3.25{col 46}{space 3}0.001{col 55}{space 3} .2944001{col 67}{space 3} 1.190935
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho41{col 14}{c |}{result}{space 2}-.3272243{col 26}{space 2} .1833483{col 37}{space 1}   -1.78{col 46}{space 3}0.074{col 55}{space 3}-.6865805{col 67}{space 3} .0321318
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho32{col 14}{c |}{result}{space 2} .9025538{col 26}{space 2} .1610531{col 37}{space 1}    5.60{col 46}{space 3}0.000{col 55}{space 3} .5868955{col 67}{space 3} 1.218212
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho42{col 14}{c |}{result}{space 2}-.6420743{col 26}{space 2} .2251437{col 37}{space 1}   -2.85{col 46}{space 3}0.004{col 55}{space 3}-1.083348{col 67}{space 3}-.2008008
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho43{col 14}{c |}{result}{space 2}-.1457431{col 26}{space 2}   .19118{col 37}{space 1}   -0.76{col 46}{space 3}0.446{col 55}{space 3}-.5204491{col 67}{space 3} .2289629
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho21{col 14}{c |}{result}{space 2} .6237264{col 26}{space 2} .1081382{col 37}{space 1}    5.77{col 46}{space 3}0.000{col 55}{space 3} .3663289{col 67}{space 3} .7924511
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho31{col 14}{c |}{result}{space 2} .6307542{col 26}{space 2} .1377188{col 37}{space 1}    4.58{col 46}{space 3}0.000{col 55}{space 3} .2861796{col 67}{space 3} .8308687
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho41{col 14}{c |}{result}{space 2}-.3160245{col 26}{space 2} .1650371{col 37}{space 1}   -1.91{col 46}{space 3}0.056{col 55}{space 3}-.5957807{col 67}{space 3} .0321208
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho32{col 14}{c |}{result}{space 2} .7175391{col 26}{space 2} .0781329{col 37}{space 1}    9.18{col 46}{space 3}0.000{col 55}{space 3} .5276591{col 67}{space 3}  .839126
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho42{col 14}{c |}{result}{space 2}-.5663103{col 26}{space 2} .1529384{col 37}{space 1}   -3.70{col 46}{space 3}0.000{col 55}{space 3}-.7944373{col 67}{space 3}-.1981448
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho43{col 14}{c |}{result}{space 2}-.1447199{col 26}{space 2}  .187176{col 37}{space 1}   -0.77{col 46}{space 3}0.439{col 55}{space 3}-.4780466{col 67}{space 3}  .225044
{txt}{hline 13}{c BT}{hline 64}
Likelihood ratio test of  rho21 = rho31 = rho41 = rho32 = rho42 = rho43 = 0:  
             chi2({res}6{txt}) = {res} 49.4399{txt}   Prob > chi2 = {res}0.0000
{txt}({res}est8{txt} stored)

{com}. 
. esttab est9 using "table5.csv", replace title(Table 4: Multivariate Probit Model) mtitles("Model 2")  obslast label se nogaps wide scalars(N Log pseudolikelihood rho2)  star(* 0.1 ** 0.05 *** 0.01) order(domestick1_lag lji_lag polity2_lag ln_gdppc_lag ln_population_lag high_conflict) 
{err}estimation result est9 not found
{txt}{search r(111), local:r(111);}

end of do-file

{search r(111), local:r(111);}

{com}. do "/var/folders/nx/zbxgl_wn39l0py84fm8z5z9c0000gn/T//SD83455.000000"
{txt}
{com}. 
. * model w/ just declines* - Table A2
. eststo: mvprobit (polpris_dec=polpris_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe time_polpris_dec_count time_polpris_dec_sq time_polpris_dec_cub)  (tort_dec=tort_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe time_tort_dec_count time_tort_dec_sq time_tort_dec_cub) (kill_dec=kill_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe time_kill_dec_count time_kill_dec_sq time_kill_dec_cub) (disap_dec=disap_lag  domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe time_disap_dec_count time_disap_dec_sq time_disap_dec_cub) (domestick1_lag=polity2_lag ln_gdppc_lag djamnestyk1_lag truthk1_lag lji_lag prev_conflict_intensity cat_rat ccpr_rat time_trial_count time_trial_sq time_trial_cub)  if all_conflict_exp==1, cluster(cowcode) dr(75)

{txt}Iteration 0:{col 16}log pseudolikelihood = {res}-2888.9526{txt}  (not concave)
Iteration 1:{col 16}log pseudolikelihood = {res}-2828.1306{txt}  (not concave)
Iteration 2:{col 16}log pseudolikelihood = {res}-2825.3693{txt}  (not concave)
Iteration 3:{col 16}log pseudolikelihood = {res}-2824.9525{txt}  (not concave)
Iteration 4:{col 16}log pseudolikelihood = {res}-2824.7721{txt}  (not concave)
Iteration 5:{col 16}log pseudolikelihood = {res}  -2824.75{txt}  (not concave)
Iteration 6:{col 16}log pseudolikelihood = {res}-2824.2578{txt}  (not concave)
Iteration 7:{col 16}log pseudolikelihood = {res}-2824.0891{txt}  (not concave)
Iteration 8:{col 16}log pseudolikelihood = {res}-2824.0138{txt}  (not concave)
Iteration 9:{col 16}log pseudolikelihood = {res}-2823.9399{txt}  (not concave)
Iteration 10:{col 16}log pseudolikelihood = {res}-2823.8646{txt}  (not concave)
Iteration 11:{col 16}log pseudolikelihood = {res}-2823.7643{txt}  (not concave)
Iteration 12:{col 16}log pseudolikelihood = {res}-2823.6186{txt}  (not concave)
Iteration 13:{col 16}log pseudolikelihood = {res}-2823.4889{txt}  (not concave)
Iteration 14:{col 16}log pseudolikelihood = {res}-2823.3587{txt}  (not concave)
Iteration 15:{col 16}log pseudolikelihood = {res} -2823.061{txt}  (not concave)
Iteration 16:{col 16}log pseudolikelihood = {res} -2822.486{txt}  (not concave)
Iteration 17:{col 16}log pseudolikelihood = {res}-2822.0493{txt}  (not concave)
Iteration 18:{col 16}log pseudolikelihood = {res}-2821.6011{txt}  (not concave)
Iteration 19:{col 16}log pseudolikelihood = {res}-2821.2408{txt}  (not concave)
Iteration 20:{col 16}log pseudolikelihood = {res} -2820.879{txt}  (not concave)
Iteration 21:{col 16}log pseudolikelihood = {res}-2820.3605{txt}  
Warning: cannot do Cholesky factorization of rho matrix
Iteration 22:{col 16}log pseudolikelihood = {res}-2819.9137{txt}  
Iteration 23:{col 16}log pseudolikelihood = {res}-2819.5434{txt}  
Iteration 24:{col 16}log pseudolikelihood = {res}-2819.5405{txt}  
Iteration 25:{col 16}log pseudolikelihood = {res}-2819.5405{txt}  
{res}
{txt}Multivariate probit (MSL, # draws = 75){col 51}Number of obs{col 67}= {res}      2041
{col 51}{help j_robustsingular:Wald chi2(70){col 67}= }         .
{txt}Log pseudolikelihood = {res}-2819.5405{col 51}{txt}Prob > chi2{col 67}= {res}         .

{txt}{ralign 89:(Std. err. adjusted for {res:86} clusters in cowcode)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      z{col 57}   P>|z|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}polpris_dec             {txt}{c |}
{space 12}polpris_lag {c |}{col 25}{res}{space 2} 1.125856{col 37}{space 2}  .109416{col 48}{space 1}   10.29{col 57}{space 3}0.000{col 65}{space 4} .9114047{col 78}{space 3} 1.340307
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2}-.7597896{col 37}{space 2} .2242674{col 48}{space 1}   -3.39{col 57}{space 3}0.001{col 65}{space 4}-1.199346{col 78}{space 3}-.3202336
{txt}{space 2}domestick1_lag_two_yr {c |}{col 25}{res}{space 2} .1902663{col 37}{space 2} .1523867{col 48}{space 1}    1.25{col 57}{space 3}0.212{col 65}{space 4}-.1084062{col 78}{space 3} .4889387
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2}-.0196767{col 37}{space 2} .0147887{col 48}{space 1}   -1.33{col 57}{space 3}0.183{col 65}{space 4} -.048662{col 78}{space 3} .0093085
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2}  .080856{col 37}{space 2} .0579198{col 48}{space 1}    1.40{col 57}{space 3}0.163{col 65}{space 4}-.0326647{col 78}{space 3} .1943766
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2} .0459907{col 37}{space 2} .0372388{col 48}{space 1}    1.24{col 57}{space 3}0.217{col 65}{space 4} -.026996{col 78}{space 3} .1189775
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2} -.700249{col 37}{space 2} .3520263{col 48}{space 1}   -1.99{col 57}{space 3}0.047{col 65}{space 4}-1.390208{col 78}{space 3}-.0102901
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2} .3577571{col 37}{space 2} .1425693{col 48}{space 1}    2.51{col 57}{space 3}0.012{col 65}{space 4} .0783264{col 78}{space 3} .6371878
{txt}{space 8}djamnestyk1_lag {c |}{col 25}{res}{space 2}-.0213258{col 37}{space 2}  .171004{col 48}{space 1}   -0.12{col 57}{space 3}0.901{col 65}{space 4}-.3564874{col 78}{space 3} .3138359
{txt}{space 12}truthk1_lag {c |}{col 25}{res}{space 2}-.2245462{col 37}{space 2} .3019008{col 48}{space 1}   -0.74{col 57}{space 3}0.457{col 65}{space 4}-.8162609{col 78}{space 3} .3671684
{txt}{space 16}cat_rat {c |}{col 25}{res}{space 2}-.1300774{col 37}{space 2} .0961297{col 48}{space 1}   -1.35{col 57}{space 3}0.176{col 65}{space 4}-.3184881{col 78}{space 3} .0583333
{txt}{space 15}ccpr_rat {c |}{col 25}{res}{space 2}-.2416125{col 37}{space 2} .1435977{col 48}{space 1}   -1.68{col 57}{space 3}0.092{col 65}{space 4}-.5230589{col 78}{space 3} .0398338
{txt}{space 17}africa {c |}{col 25}{res}{space 2} .5572117{col 37}{space 2} .1789519{col 48}{space 1}    3.11{col 57}{space 3}0.002{col 65}{space 4} .2064723{col 78}{space 3} .9079511
{txt}{space 19}asia {c |}{col 25}{res}{space 2} .7990994{col 37}{space 2} .1713015{col 48}{space 1}    4.66{col 57}{space 3}0.000{col 65}{space 4} .4633546{col 78}{space 3} 1.134844
{txt}{space 17}europe {c |}{col 25}{res}{space 2} .0427265{col 37}{space 2} .1536343{col 48}{space 1}    0.28{col 57}{space 3}0.781{col 65}{space 4}-.2583912{col 78}{space 3} .3438442
{txt}{space 1}time_polpris_dec_count {c |}{col 25}{res}{space 2} .0200781{col 37}{space 2} .0160052{col 48}{space 1}    1.25{col 57}{space 3}0.210{col 65}{space 4}-.0112916{col 78}{space 3} .0514478
{txt}{space 4}time_polpris_dec_sq {c |}{col 25}{res}{space 2}-.0115613{col 37}{space 2} .0027186{col 48}{space 1}   -4.25{col 57}{space 3}0.000{col 65}{space 4}-.0168897{col 78}{space 3}-.0062328
{txt}{space 3}time_polpris_dec_cub {c |}{col 25}{res}{space 2} .0003481{col 37}{space 2}  .000084{col 48}{space 1}    4.15{col 57}{space 3}0.000{col 65}{space 4} .0001836{col 78}{space 3} .0005127
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-3.299483{col 37}{space 2} .7163802{col 48}{space 1}   -4.61{col 57}{space 3}0.000{col 65}{space 4}-4.703562{col 78}{space 3}-1.895404
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}tort_dec                {txt}{c |}
{space 15}tort_lag {c |}{col 25}{res}{space 2} 1.617733{col 37}{space 2} .1502043{col 48}{space 1}   10.77{col 57}{space 3}0.000{col 65}{space 4} 1.323338{col 78}{space 3} 1.912128
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2}-.9751037{col 37}{space 2} .4379418{col 48}{space 1}   -2.23{col 57}{space 3}0.026{col 65}{space 4}-1.833454{col 78}{space 3}-.1167535
{txt}{space 2}domestick1_lag_two_yr {c |}{col 25}{res}{space 2} .1747175{col 37}{space 2} .1945135{col 48}{space 1}    0.90{col 57}{space 3}0.369{col 65}{space 4}-.2065219{col 78}{space 3}  .555957
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2}-.0087067{col 37}{space 2} .0140581{col 48}{space 1}   -0.62{col 57}{space 3}0.536{col 65}{space 4}-.0362601{col 78}{space 3} .0188468
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2} -.006434{col 37}{space 2} .0870213{col 48}{space 1}   -0.07{col 57}{space 3}0.941{col 65}{space 4}-.1769926{col 78}{space 3} .1641246
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2} .1512484{col 37}{space 2} .0622303{col 48}{space 1}    2.43{col 57}{space 3}0.015{col 65}{space 4} .0292793{col 78}{space 3} .2732175
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2}-.8394828{col 37}{space 2} .5217844{col 48}{space 1}   -1.61{col 57}{space 3}0.108{col 65}{space 4}-1.862161{col 78}{space 3} .1831958
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2} .4233569{col 37}{space 2} .0963922{col 48}{space 1}    4.39{col 57}{space 3}0.000{col 65}{space 4} .2344317{col 78}{space 3}  .612282
{txt}{space 8}djamnestyk1_lag {c |}{col 25}{res}{space 2}  .136812{col 37}{space 2} .1733697{col 48}{space 1}    0.79{col 57}{space 3}0.430{col 65}{space 4}-.2029864{col 78}{space 3} .4766105
{txt}{space 12}truthk1_lag {c |}{col 25}{res}{space 2}-.2391205{col 37}{space 2} .3594974{col 48}{space 1}   -0.67{col 57}{space 3}0.506{col 65}{space 4}-.9437225{col 78}{space 3} .4654815
{txt}{space 16}cat_rat {c |}{col 25}{res}{space 2} .1477125{col 37}{space 2}  .126963{col 48}{space 1}    1.16{col 57}{space 3}0.245{col 65}{space 4}-.1011303{col 78}{space 3} .3965553
{txt}{space 15}ccpr_rat {c |}{col 25}{res}{space 2} .1025758{col 37}{space 2} .1739349{col 48}{space 1}    0.59{col 57}{space 3}0.555{col 65}{space 4}-.2383304{col 78}{space 3}  .443482
{txt}{space 17}africa {c |}{col 25}{res}{space 2}-.1143117{col 37}{space 2} .2358994{col 48}{space 1}   -0.48{col 57}{space 3}0.628{col 65}{space 4}-.5766661{col 78}{space 3} .3480427
{txt}{space 19}asia {c |}{col 25}{res}{space 2}-.1521732{col 37}{space 2} .2532903{col 48}{space 1}   -0.60{col 57}{space 3}0.548{col 65}{space 4}-.6486132{col 78}{space 3} .3442667
{txt}{space 17}europe {c |}{col 25}{res}{space 2}-.2317746{col 37}{space 2} .2861582{col 48}{space 1}   -0.81{col 57}{space 3}0.418{col 65}{space 4}-.7926343{col 78}{space 3} .3290851
{txt}{space 4}time_tort_dec_count {c |}{col 25}{res}{space 2}-.0130842{col 37}{space 2} .0102234{col 48}{space 1}   -1.28{col 57}{space 3}0.201{col 65}{space 4}-.0331216{col 78}{space 3} .0069532
{txt}{space 7}time_tort_dec_sq {c |}{col 25}{res}{space 2}-.0109121{col 37}{space 2} .0026734{col 48}{space 1}   -4.08{col 57}{space 3}0.000{col 65}{space 4}-.0161519{col 78}{space 3}-.0056723
{txt}{space 6}time_tort_dec_cub {c |}{col 25}{res}{space 2} .0003761{col 37}{space 2}  .000088{col 48}{space 1}    4.27{col 57}{space 3}0.000{col 65}{space 4} .0002036{col 78}{space 3} .0005486
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-4.178731{col 37}{space 2} 1.263266{col 48}{space 1}   -3.31{col 57}{space 3}0.001{col 65}{space 4}-6.654686{col 78}{space 3}-1.702775
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}kill_dec                {txt}{c |}
{space 15}kill_lag {c |}{col 25}{res}{space 2} 1.139719{col 37}{space 2} .0839312{col 48}{space 1}   13.58{col 57}{space 3}0.000{col 65}{space 4} .9752165{col 78}{space 3} 1.304221
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2}-.2572777{col 37}{space 2} .4367866{col 48}{space 1}   -0.59{col 57}{space 3}0.556{col 65}{space 4}-1.113364{col 78}{space 3} .5988082
{txt}{space 2}domestick1_lag_two_yr {c |}{col 25}{res}{space 2}-.2591049{col 37}{space 2}  .150946{col 48}{space 1}   -1.72{col 57}{space 3}0.086{col 65}{space 4}-.5549537{col 78}{space 3} .0367439
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0268651{col 37}{space 2}  .013973{col 48}{space 1}    1.92{col 57}{space 3}0.055{col 65}{space 4}-.0005215{col 78}{space 3} .0542517
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2} .0120855{col 37}{space 2} .0621801{col 48}{space 1}    0.19{col 57}{space 3}0.846{col 65}{space 4}-.1097852{col 78}{space 3} .1339562
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2}  .226015{col 37}{space 2} .0452464{col 48}{space 1}    5.00{col 57}{space 3}0.000{col 65}{space 4} .1373336{col 78}{space 3} .3146964
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2}-.9357242{col 37}{space 2} .4688921{col 48}{space 1}   -2.00{col 57}{space 3}0.046{col 65}{space 4}-1.854736{col 78}{space 3}-.0167126
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2} .7007585{col 37}{space 2} .1386092{col 48}{space 1}    5.06{col 57}{space 3}0.000{col 65}{space 4} .4290894{col 78}{space 3} .9724275
{txt}{space 8}djamnestyk1_lag {c |}{col 25}{res}{space 2} .3123681{col 37}{space 2}  .150371{col 48}{space 1}    2.08{col 57}{space 3}0.038{col 65}{space 4} .0176464{col 78}{space 3} .6070899
{txt}{space 12}truthk1_lag {c |}{col 25}{res}{space 2} .2098055{col 37}{space 2} .2853693{col 48}{space 1}    0.74{col 57}{space 3}0.462{col 65}{space 4}-.3495081{col 78}{space 3} .7691192
{txt}{space 16}cat_rat {c |}{col 25}{res}{space 2}-.0212141{col 37}{space 2} .0991256{col 48}{space 1}   -0.21{col 57}{space 3}0.831{col 65}{space 4}-.2154967{col 78}{space 3} .1730686
{txt}{space 15}ccpr_rat {c |}{col 25}{res}{space 2}  .054951{col 37}{space 2} .1351544{col 48}{space 1}    0.41{col 57}{space 3}0.684{col 65}{space 4}-.2099467{col 78}{space 3} .3198487
{txt}{space 17}africa {c |}{col 25}{res}{space 2} .1240819{col 37}{space 2} .1751976{col 48}{space 1}    0.71{col 57}{space 3}0.479{col 65}{space 4} -.219299{col 78}{space 3} .4674629
{txt}{space 19}asia {c |}{col 25}{res}{space 2} .0825092{col 37}{space 2} .1942352{col 48}{space 1}    0.42{col 57}{space 3}0.671{col 65}{space 4}-.2981847{col 78}{space 3} .4632032
{txt}{space 17}europe {c |}{col 25}{res}{space 2}-.6276087{col 37}{space 2} .1420094{col 48}{space 1}   -4.42{col 57}{space 3}0.000{col 65}{space 4}-.9059421{col 78}{space 3}-.3492754
{txt}{space 4}time_kill_dec_count {c |}{col 25}{res}{space 2}  .024781{col 37}{space 2} .0142825{col 48}{space 1}    1.74{col 57}{space 3}0.083{col 65}{space 4}-.0032122{col 78}{space 3} .0527742
{txt}{space 7}time_kill_dec_sq {c |}{col 25}{res}{space 2}-.0125622{col 37}{space 2} .0025994{col 48}{space 1}   -4.83{col 57}{space 3}0.000{col 65}{space 4} -.017657{col 78}{space 3}-.0074675
{txt}{space 6}time_kill_dec_cub {c |}{col 25}{res}{space 2} .0005009{col 37}{space 2}  .000108{col 48}{space 1}    4.64{col 57}{space 3}0.000{col 65}{space 4} .0002893{col 78}{space 3} .0007125
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-5.879077{col 37}{space 2}  .760702{col 48}{space 1}   -7.73{col 57}{space 3}0.000{col 65}{space 4}-7.370025{col 78}{space 3}-4.388128
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}disap_dec               {txt}{c |}
{space 14}disap_lag {c |}{col 25}{res}{space 2} .6453243{col 37}{space 2} .0681312{col 48}{space 1}    9.47{col 57}{space 3}0.000{col 65}{space 4} .5117895{col 78}{space 3}  .778859
{txt}{space 9}domestick1_lag {c |}{col 25}{res}{space 2} 1.280073{col 37}{space 2} .3562227{col 48}{space 1}    3.59{col 57}{space 3}0.000{col 65}{space 4} .5818891{col 78}{space 3} 1.978256
{txt}{space 2}domestick1_lag_two_yr {c |}{col 25}{res}{space 2}-.0536929{col 37}{space 2} .2291704{col 48}{space 1}   -0.23{col 57}{space 3}0.815{col 65}{space 4}-.5028585{col 78}{space 3} .3954728
{txt}{space 12}polity2_lag {c |}{col 25}{res}{space 2}-.0081736{col 37}{space 2} .0133734{col 48}{space 1}   -0.61{col 57}{space 3}0.541{col 65}{space 4}-.0343849{col 78}{space 3} .0180378
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2}-.0539072{col 37}{space 2} .0500808{col 48}{space 1}   -1.08{col 57}{space 3}0.282{col 65}{space 4}-.1520637{col 78}{space 3} .0442494
{txt}{space 6}ln_population_lag {c |}{col 25}{res}{space 2} .1364282{col 37}{space 2} .0344214{col 48}{space 1}    3.96{col 57}{space 3}0.000{col 65}{space 4} .0689635{col 78}{space 3} .2038929
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2}-.4474184{col 37}{space 2}  .357541{col 48}{space 1}   -1.25{col 57}{space 3}0.211{col 65}{space 4}-1.148186{col 78}{space 3} .2533491
{txt}{space 10}high_conflict {c |}{col 25}{res}{space 2} .7624661{col 37}{space 2} .1310517{col 48}{space 1}    5.82{col 57}{space 3}0.000{col 65}{space 4} .5056095{col 78}{space 3} 1.019323
{txt}{space 8}djamnestyk1_lag {c |}{col 25}{res}{space 2} .3272267{col 37}{space 2} .1290542{col 48}{space 1}    2.54{col 57}{space 3}0.011{col 65}{space 4} .0742852{col 78}{space 3} .5801683
{txt}{space 12}truthk1_lag {c |}{col 25}{res}{space 2} .0148964{col 37}{space 2} .2674843{col 48}{space 1}    0.06{col 57}{space 3}0.956{col 65}{space 4}-.5093632{col 78}{space 3}  .539156
{txt}{space 16}cat_rat {c |}{col 25}{res}{space 2} -.134431{col 37}{space 2} .1068093{col 48}{space 1}   -1.26{col 57}{space 3}0.208{col 65}{space 4}-.3437733{col 78}{space 3} .0749113
{txt}{space 15}ccpr_rat {c |}{col 25}{res}{space 2} .0028066{col 37}{space 2} .1404151{col 48}{space 1}    0.02{col 57}{space 3}0.984{col 65}{space 4} -.272402{col 78}{space 3} .2780151
{txt}{space 17}africa {c |}{col 25}{res}{space 2}-.0436537{col 37}{space 2} .1400088{col 48}{space 1}   -0.31{col 57}{space 3}0.755{col 65}{space 4}-.3180659{col 78}{space 3} .2307585
{txt}{space 19}asia {c |}{col 25}{res}{space 2} .0330167{col 37}{space 2} .1498903{col 48}{space 1}    0.22{col 57}{space 3}0.826{col 65}{space 4}-.2607629{col 78}{space 3} .3267962
{txt}{space 17}europe {c |}{col 25}{res}{space 2}-.4189491{col 37}{space 2} .2213545{col 48}{space 1}   -1.89{col 57}{space 3}0.058{col 65}{space 4} -.852796{col 78}{space 3} .0148978
{txt}{space 3}time_disap_dec_count {c |}{col 25}{res}{space 2}-.0100173{col 37}{space 2} .0112993{col 48}{space 1}   -0.89{col 57}{space 3}0.375{col 65}{space 4}-.0321635{col 78}{space 3} .0121288
{txt}{space 6}time_disap_dec_sq {c |}{col 25}{res}{space 2}-.0037939{col 37}{space 2}  .001645{col 48}{space 1}   -2.31{col 57}{space 3}0.021{col 65}{space 4}-.0070181{col 78}{space 3}-.0005696
{txt}{space 5}time_disap_dec_cub {c |}{col 25}{res}{space 2} .0001311{col 37}{space 2} .0000536{col 48}{space 1}    2.44{col 57}{space 3}0.015{col 65}{space 4}  .000026{col 78}{space 3} .0002362
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-3.713405{col 37}{space 2} .6186126{col 48}{space 1}   -6.00{col 57}{space 3}0.000{col 65}{space 4}-4.925864{col 78}{space 3}-2.500947
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}domestick1_lag          {txt}{c |}
{space 12}polity2_lag {c |}{col 25}{res}{space 2} .0321464{col 37}{space 2} .0116498{col 48}{space 1}    2.76{col 57}{space 3}0.006{col 65}{space 4} .0093132{col 78}{space 3} .0549796
{txt}{space 11}ln_gdppc_lag {c |}{col 25}{res}{space 2}  .080644{col 37}{space 2} .0749804{col 48}{space 1}    1.08{col 57}{space 3}0.282{col 65}{space 4}-.0663148{col 78}{space 3} .2276028
{txt}{space 8}djamnestyk1_lag {c |}{col 25}{res}{space 2} .2364262{col 37}{space 2}  .146305{col 48}{space 1}    1.62{col 57}{space 3}0.106{col 65}{space 4}-.0503263{col 78}{space 3} .5231787
{txt}{space 12}truthk1_lag {c |}{col 25}{res}{space 2} .6346409{col 37}{space 2}  .281278{col 48}{space 1}    2.26{col 57}{space 3}0.024{col 65}{space 4} .0833462{col 78}{space 3} 1.185936
{txt}{space 16}lji_lag {c |}{col 25}{res}{space 2}-.7969659{col 37}{space 2} .3484784{col 48}{space 1}   -2.29{col 57}{space 3}0.022{col 65}{space 4}-1.479971{col 78}{space 3}-.1139607
{txt}prev_conflict_intensity {c |}{col 25}{res}{space 2} .0352257{col 37}{space 2} .1307074{col 48}{space 1}    0.27{col 57}{space 3}0.788{col 65}{space 4}-.2209561{col 78}{space 3} .2914074
{txt}{space 16}cat_rat {c |}{col 25}{res}{space 2} .0619162{col 37}{space 2} .1580554{col 48}{space 1}    0.39{col 57}{space 3}0.695{col 65}{space 4}-.2478667{col 78}{space 3}  .371699
{txt}{space 15}ccpr_rat {c |}{col 25}{res}{space 2}-.0244503{col 37}{space 2} .1685874{col 48}{space 1}   -0.15{col 57}{space 3}0.885{col 65}{space 4}-.3548755{col 78}{space 3} .3059749
{txt}{space 7}time_trial_count {c |}{col 25}{res}{space 2}-.1180584{col 37}{space 2}  .043176{col 48}{space 1}   -2.73{col 57}{space 3}0.006{col 65}{space 4}-.2026817{col 78}{space 3}-.0334351
{txt}{space 10}time_trial_sq {c |}{col 25}{res}{space 2} .0072021{col 37}{space 2}  .003416{col 48}{space 1}    2.11{col 57}{space 3}0.035{col 65}{space 4} .0005068{col 78}{space 3} .0138974
{txt}{space 9}time_trial_cub {c |}{col 25}{res}{space 2}-.0001439{col 37}{space 2} .0000787{col 48}{space 1}   -1.83{col 57}{space 3}0.067{col 65}{space 4} -.000298{col 78}{space 3} .0000103
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}-1.629809{col 37}{space 2} .4466507{col 48}{space 1}   -3.65{col 57}{space 3}0.000{col 65}{space 4}-2.505228{col 78}{space 3}-.7543895
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{col 1}{text}    /atrho21{col 14}{c |}{result}{space 2} .3490976{col 26}{space 2} .0923293{col 37}{space 1}    3.78{col 46}{space 3}0.000{col 55}{space 3} .1681355{col 67}{space 3} .5300597
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho31{col 14}{c |}{result}{space 2} .3232968{col 26}{space 2} .0829592{col 37}{space 1}    3.90{col 46}{space 3}0.000{col 55}{space 3} .1606998{col 67}{space 3} .4858938
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho41{col 14}{c |}{result}{space 2} .1990354{col 26}{space 2} .0744474{col 37}{space 1}    2.67{col 46}{space 3}0.008{col 55}{space 3} .0531211{col 67}{space 3} .3449496
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho51{col 14}{c |}{result}{space 2}  .585478{col 26}{space 2} .1412393{col 37}{space 1}    4.15{col 46}{space 3}0.000{col 55}{space 3}  .308654{col 67}{space 3} .8623019
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho32{col 14}{c |}{result}{space 2} .5179923{col 26}{space 2} .0811997{col 37}{space 1}    6.38{col 46}{space 3}0.000{col 55}{space 3} .3588438{col 67}{space 3} .6771408
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho42{col 14}{c |}{result}{space 2} .2246775{col 26}{space 2} .0772095{col 37}{space 1}    2.91{col 46}{space 3}0.004{col 55}{space 3} .0733497{col 67}{space 3} .3760053
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho52{col 14}{c |}{result}{space 2} .4929782{col 26}{space 2} .1993856{col 37}{space 1}    2.47{col 46}{space 3}0.013{col 55}{space 3} .1021897{col 67}{space 3} .8837668
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho43{col 14}{c |}{result}{space 2} .3688218{col 26}{space 2} .0844205{col 37}{space 1}    4.37{col 46}{space 3}0.000{col 55}{space 3} .2033606{col 67}{space 3} .5342829
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho53{col 14}{c |}{result}{space 2} .2859992{col 26}{space 2} .2095463{col 37}{space 1}    1.36{col 46}{space 3}0.172{col 55}{space 3} -.124704{col 67}{space 3} .6967025
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho54{col 14}{c |}{result}{space 2}-.6207886{col 26}{space 2}  .157052{col 37}{space 1}   -3.95{col 46}{space 3}0.000{col 55}{space 3}-.9286048{col 67}{space 3}-.3129724
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho21{col 14}{c |}{result}{space 2}  .335575{col 26}{space 2}  .081932{col 37}{space 1}    4.10{col 46}{space 3}0.000{col 55}{space 3} .1665689{col 67}{space 3} .4854267
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho31{col 14}{c |}{result}{space 2} .3124848{col 26}{space 2} .0748585{col 37}{space 1}    4.17{col 46}{space 3}0.000{col 55}{space 3} .1593306{col 67}{space 3} .4509513
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho41{col 14}{c |}{result}{space 2} .1964481{col 26}{space 2} .0715744{col 37}{space 1}    2.74{col 46}{space 3}0.006{col 55}{space 3} .0530712{col 67}{space 3}  .331889
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho51{col 14}{c |}{result}{space 2} .5266355{col 26}{space 2} .1020673{col 37}{space 1}    5.16{col 46}{space 3}0.000{col 55}{space 3} .2992121{col 67}{space 3} .6974418
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho32{col 14}{c |}{result}{space 2}  .476149{col 26}{space 2} .0627903{col 37}{space 1}    7.58{col 46}{space 3}0.000{col 55}{space 3} .3441952{col 67}{space 3} .5896575
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho42{col 14}{c |}{result}{space 2} .2209717{col 26}{space 2} .0734395{col 37}{space 1}    3.01{col 46}{space 3}0.003{col 55}{space 3} .0732184{col 67}{space 3} .3592333
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho52{col 14}{c |}{result}{space 2}  .456577{col 26}{space 2} .1578212{col 37}{space 1}    2.89{col 46}{space 3}0.004{col 55}{space 3} .1018354{col 67}{space 3} .7083014
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho43{col 14}{c |}{result}{space 2} .3529607{col 26}{space 2} .0739033{col 37}{space 1}    4.78{col 46}{space 3}0.000{col 55}{space 3} .2006029{col 67}{space 3} .4886481
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho53{col 14}{c |}{result}{space 2} .2784484{col 26}{space 2} .1932995{col 37}{space 1}    1.44{col 46}{space 3}0.150{col 55}{space 3}-.1240616{col 67}{space 3} .6022705
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho54{col 14}{c |}{result}{space 2}-.5516768{col 26}{space 2} .1092536{col 37}{space 1}   -5.05{col 46}{space 3}0.000{col 55}{space 3}-.7299427{col 67}{space 3}-.3031388
{txt}{hline 13}{c BT}{hline 64}
Likelihood ratio test of  rho21 = rho31 = rho41 = rho51 = rho32 = rho42 = rho52 = rho43 = rho53 = rho54 = 0:  
             chi2({res}10{txt}) = {res} 138.824{txt}   Prob > chi2 = {res}0.0000
{txt}({res}est9{txt} stored)

{com}. 
. 
. 
. * loser-targeted-with trial - Table A3*
. 
. eststo: mvprobit (polpris_imp=polpris_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_polpris_count time_polpris_sq time_polpris_cub)  (tort_imp=tort_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_tort_count time_tort_sq time_tort_cub) (kill_imp=kill_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_kill_count time_kill_sq time_kill_cub) (disap_imp=disap_lag  domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_disap_count time_disap_sq time_disap_cub) (loser_both_targ_trial=polity2_lag ln_gdppc_lag djamnestyk1_lag truthk1_lag lji_lag prev_conflict_intensity cat_rat ccpr_rat time_targ_loser_both_count time_targ_loser_both_count_sq time_targ_loser_both_count_cub)  if all_conflict_exp==1, cluster(cowcode) dr(75)

{txt}Iteration 0:{col 16}log pseudolikelihood = {res}  -2980.65{txt}  
Iteration 1:{col 16}log pseudolikelihood = {res}-2929.7354{txt}  
Iteration 2:{col 16}log pseudolikelihood = {res}-2926.9998{txt}  
Iteration 3:{col 16}log pseudolikelihood = {res}-2926.9879{txt}  
Iteration 4:{col 16}log pseudolikelihood = {res}-2926.9879{txt}  
{res}
{txt}Multivariate probit (MSL, # draws = 75){col 51}Number of obs{col 67}= {res}      2041
{col 51}{help j_robustsingular:Wald chi2(70){col 67}= }         .
{txt}Log pseudolikelihood = {res}-2926.9879{col 51}{txt}Prob > chi2{col 67}= {res}         .

{txt}{ralign 96:(Std. err. adjusted for {res:86} clusters in cowcode)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      z{col 64}   P>|z|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}polpris_imp                    {txt}{c |}
{space 19}polpris_lag {c |}{col 32}{res}{space 2}-1.053258{col 44}{space 2} .0821783{col 55}{space 1}  -12.82{col 64}{space 3}0.000{col 72}{space 4}-1.214325{col 85}{space 3}-.8921914
{txt}{space 16}domestick1_lag {c |}{col 32}{res}{space 2} .4165182{col 44}{space 2} .1441955{col 55}{space 1}    2.89{col 64}{space 3}0.004{col 72}{space 4} .1339002{col 85}{space 3} .6991362
{txt}{space 9}domestick1_lag_two_yr {c |}{col 32}{res}{space 2}-.2601672{col 44}{space 2}  .242574{col 55}{space 1}   -1.07{col 64}{space 3}0.283{col 72}{space 4}-.7356036{col 85}{space 3} .2152691
{txt}{space 19}polity2_lag {c |}{col 32}{res}{space 2} .0604459{col 44}{space 2} .0125817{col 55}{space 1}    4.80{col 64}{space 3}0.000{col 72}{space 4} .0357861{col 85}{space 3} .0851056
{txt}{space 18}ln_gdppc_lag {c |}{col 32}{res}{space 2}-.0788166{col 44}{space 2} .0628812{col 55}{space 1}   -1.25{col 64}{space 3}0.210{col 72}{space 4}-.2020614{col 85}{space 3} .0444283
{txt}{space 13}ln_population_lag {c |}{col 32}{res}{space 2}-.2044295{col 44}{space 2} .0365845{col 55}{space 1}   -5.59{col 64}{space 3}0.000{col 72}{space 4}-.2761338{col 85}{space 3}-.1327253
{txt}{space 23}lji_lag {c |}{col 32}{res}{space 2} .1481885{col 44}{space 2}   .35083{col 55}{space 1}    0.42{col 64}{space 3}0.673{col 72}{space 4}-.5394257{col 85}{space 3} .8358028
{txt}{space 17}high_conflict {c |}{col 32}{res}{space 2}-.5107295{col 44}{space 2} .1708903{col 55}{space 1}   -2.99{col 64}{space 3}0.003{col 72}{space 4}-.8456684{col 85}{space 3}-.1757906
{txt}{space 15}djamnestyk1_lag {c |}{col 32}{res}{space 2} .0596311{col 44}{space 2} .1366856{col 55}{space 1}    0.44{col 64}{space 3}0.663{col 72}{space 4}-.2082678{col 85}{space 3} .3275299
{txt}{space 19}truthk1_lag {c |}{col 32}{res}{space 2} .3822107{col 44}{space 2}  .271538{col 55}{space 1}    1.41{col 64}{space 3}0.159{col 72}{space 4} -.149994{col 85}{space 3} .9144154
{txt}{space 23}cat_rat {c |}{col 32}{res}{space 2}-.0339349{col 44}{space 2} .1096596{col 55}{space 1}   -0.31{col 64}{space 3}0.757{col 72}{space 4}-.2488638{col 85}{space 3}  .180994
{txt}{space 22}ccpr_rat {c |}{col 32}{res}{space 2}-.2877108{col 44}{space 2} .1386309{col 55}{space 1}   -2.08{col 64}{space 3}0.038{col 72}{space 4}-.5594224{col 85}{space 3}-.0159993
{txt}{space 24}africa {c |}{col 32}{res}{space 2}-.1146535{col 44}{space 2} .1649699{col 55}{space 1}   -0.69{col 64}{space 3}0.487{col 72}{space 4}-.4379885{col 85}{space 3} .2086814
{txt}{space 26}asia {c |}{col 32}{res}{space 2}-.4234684{col 44}{space 2} .1542495{col 55}{space 1}   -2.75{col 64}{space 3}0.006{col 72}{space 4}-.7257919{col 85}{space 3}-.1211449
{txt}{space 24}europe {c |}{col 32}{res}{space 2} .2155617{col 44}{space 2} .2251358{col 55}{space 1}    0.96{col 64}{space 3}0.338{col 72}{space 4}-.2256964{col 85}{space 3} .6568198
{txt}{space 12}time_polpris_count {c |}{col 32}{res}{space 2}-.0393844{col 44}{space 2} .0416811{col 55}{space 1}   -0.94{col 64}{space 3}0.345{col 72}{space 4}-.1210779{col 85}{space 3} .0423091
{txt}{space 15}time_polpris_sq {c |}{col 32}{res}{space 2}-.0004596{col 44}{space 2} .0048641{col 55}{space 1}   -0.09{col 64}{space 3}0.925{col 72}{space 4} -.009993{col 85}{space 3} .0090737
{txt}{space 14}time_polpris_cub {c |}{col 32}{res}{space 2}   .00005{col 44}{space 2} .0001294{col 55}{space 1}    0.39{col 64}{space 3}0.699{col 72}{space 4}-.0002037{col 85}{space 3} .0003037
{txt}{space 25}_cons {c |}{col 32}{res}{space 2}   3.9804{col 44}{space 2} .7591169{col 55}{space 1}    5.24{col 64}{space 3}0.000{col 72}{space 4} 2.492559{col 85}{space 3} 5.468242
{txt}{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}tort_imp                       {txt}{c |}
{space 22}tort_lag {c |}{col 32}{res}{space 2}-1.104829{col 44}{space 2} .0951449{col 55}{space 1}  -11.61{col 64}{space 3}0.000{col 72}{space 4} -1.29131{col 85}{space 3}-.9183487
{txt}{space 16}domestick1_lag {c |}{col 32}{res}{space 2}-.2673092{col 44}{space 2} .2008459{col 55}{space 1}   -1.33{col 64}{space 3}0.183{col 72}{space 4}  -.66096{col 85}{space 3} .1263416
{txt}{space 9}domestick1_lag_two_yr {c |}{col 32}{res}{space 2}-.3546676{col 44}{space 2} .1707773{col 55}{space 1}   -2.08{col 64}{space 3}0.038{col 72}{space 4}-.6893851{col 85}{space 3}-.0199502
{txt}{space 19}polity2_lag {c |}{col 32}{res}{space 2} .0081685{col 44}{space 2}  .014434{col 55}{space 1}    0.57{col 64}{space 3}0.571{col 72}{space 4}-.0201216{col 85}{space 3} .0364587
{txt}{space 18}ln_gdppc_lag {c |}{col 32}{res}{space 2} .0228618{col 44}{space 2}   .05835{col 55}{space 1}    0.39{col 64}{space 3}0.695{col 72}{space 4}-.0915021{col 85}{space 3} .1372257
{txt}{space 13}ln_population_lag {c |}{col 32}{res}{space 2}-.1512054{col 44}{space 2} .0368452{col 55}{space 1}   -4.10{col 64}{space 3}0.000{col 72}{space 4}-.2234206{col 85}{space 3}-.0789902
{txt}{space 23}lji_lag {c |}{col 32}{res}{space 2} .6640815{col 44}{space 2} .3642835{col 55}{space 1}    1.82{col 64}{space 3}0.068{col 72}{space 4} -.049901{col 85}{space 3} 1.378064
{txt}{space 17}high_conflict {c |}{col 32}{res}{space 2}-.3875561{col 44}{space 2} .1727375{col 55}{space 1}   -2.24{col 64}{space 3}0.025{col 72}{space 4}-.7261154{col 85}{space 3}-.0489967
{txt}{space 15}djamnestyk1_lag {c |}{col 32}{res}{space 2} .0284271{col 44}{space 2} .1413245{col 55}{space 1}    0.20{col 64}{space 3}0.841{col 72}{space 4}-.2485638{col 85}{space 3} .3054181
{txt}{space 19}truthk1_lag {c |}{col 32}{res}{space 2} .7137983{col 44}{space 2} .2602677{col 55}{space 1}    2.74{col 64}{space 3}0.006{col 72}{space 4} .2036831{col 85}{space 3} 1.223914
{txt}{space 23}cat_rat {c |}{col 32}{res}{space 2}-.3005664{col 44}{space 2} .1030531{col 55}{space 1}   -2.92{col 64}{space 3}0.004{col 72}{space 4}-.5025468{col 85}{space 3} -.098586
{txt}{space 22}ccpr_rat {c |}{col 32}{res}{space 2}-.2471025{col 44}{space 2} .1154358{col 55}{space 1}   -2.14{col 64}{space 3}0.032{col 72}{space 4}-.4733525{col 85}{space 3}-.0208525
{txt}{space 24}africa {c |}{col 32}{res}{space 2} .1089855{col 44}{space 2} .1494038{col 55}{space 1}    0.73{col 64}{space 3}0.466{col 72}{space 4}-.1838405{col 85}{space 3} .4018116
{txt}{space 26}asia {c |}{col 32}{res}{space 2}-.1578866{col 44}{space 2} .1639861{col 55}{space 1}   -0.96{col 64}{space 3}0.336{col 72}{space 4}-.4792934{col 85}{space 3} .1635203
{txt}{space 24}europe {c |}{col 32}{res}{space 2} .4956135{col 44}{space 2} .1622308{col 55}{space 1}    3.05{col 64}{space 3}0.002{col 72}{space 4}  .177647{col 85}{space 3}   .81358
{txt}{space 15}time_tort_count {c |}{col 32}{res}{space 2}-.0457078{col 44}{space 2} .0373149{col 55}{space 1}   -1.22{col 64}{space 3}0.221{col 72}{space 4}-.1188436{col 85}{space 3}  .027428
{txt}{space 18}time_tort_sq {c |}{col 32}{res}{space 2}-.0004554{col 44}{space 2} .0035402{col 55}{space 1}   -0.13{col 64}{space 3}0.898{col 72}{space 4} -.007394{col 85}{space 3} .0064832
{txt}{space 17}time_tort_cub {c |}{col 32}{res}{space 2} .0000485{col 44}{space 2} .0000909{col 55}{space 1}    0.53{col 64}{space 3}0.594{col 72}{space 4}-.0001297{col 85}{space 3} .0002267
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} 1.908149{col 44}{space 2} .7176373{col 55}{space 1}    2.66{col 64}{space 3}0.008{col 72}{space 4} .5016058{col 85}{space 3} 3.314692
{txt}{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}kill_imp                       {txt}{c |}
{space 22}kill_lag {c |}{col 32}{res}{space 2}-.9958242{col 44}{space 2} .0850665{col 55}{space 1}  -11.71{col 64}{space 3}0.000{col 72}{space 4}-1.162552{col 85}{space 3}-.8290969
{txt}{space 16}domestick1_lag {c |}{col 32}{res}{space 2} .0433124{col 44}{space 2} .1649874{col 55}{space 1}    0.26{col 64}{space 3}0.793{col 72}{space 4} -.280057{col 85}{space 3} .3666817
{txt}{space 9}domestick1_lag_two_yr {c |}{col 32}{res}{space 2} -.025815{col 44}{space 2} .1763431{col 55}{space 1}   -0.15{col 64}{space 3}0.884{col 72}{space 4}-.3714412{col 85}{space 3} .3198111
{txt}{space 19}polity2_lag {c |}{col 32}{res}{space 2}-.0539594{col 44}{space 2} .0150244{col 55}{space 1}   -3.59{col 64}{space 3}0.000{col 72}{space 4}-.0834066{col 85}{space 3}-.0245122
{txt}{space 18}ln_gdppc_lag {c |}{col 32}{res}{space 2}-.0601972{col 44}{space 2} .0624167{col 55}{space 1}   -0.96{col 64}{space 3}0.335{col 72}{space 4}-.1825317{col 85}{space 3} .0621374
{txt}{space 13}ln_population_lag {c |}{col 32}{res}{space 2}-.1680969{col 44}{space 2} .0353758{col 55}{space 1}   -4.75{col 64}{space 3}0.000{col 72}{space 4}-.2374322{col 85}{space 3}-.0987615
{txt}{space 23}lji_lag {c |}{col 32}{res}{space 2} 1.342316{col 44}{space 2} .4023546{col 55}{space 1}    3.34{col 64}{space 3}0.001{col 72}{space 4} .5537158{col 85}{space 3} 2.130917
{txt}{space 17}high_conflict {c |}{col 32}{res}{space 2}-.7983953{col 44}{space 2} .1384864{col 55}{space 1}   -5.77{col 64}{space 3}0.000{col 72}{space 4}-1.069824{col 85}{space 3} -.526967
{txt}{space 15}djamnestyk1_lag {c |}{col 32}{res}{space 2}-.1761254{col 44}{space 2} .1571127{col 55}{space 1}   -1.12{col 64}{space 3}0.262{col 72}{space 4}-.4840607{col 85}{space 3}   .13181
{txt}{space 19}truthk1_lag {c |}{col 32}{res}{space 2}   .03166{col 44}{space 2} .2862893{col 55}{space 1}    0.11{col 64}{space 3}0.912{col 72}{space 4}-.5294567{col 85}{space 3} .5927768
{txt}{space 23}cat_rat {c |}{col 32}{res}{space 2} .0513145{col 44}{space 2} .1246168{col 55}{space 1}    0.41{col 64}{space 3}0.681{col 72}{space 4}-.1929299{col 85}{space 3} .2955589
{txt}{space 22}ccpr_rat {c |}{col 32}{res}{space 2}-.0263442{col 44}{space 2} .1617965{col 55}{space 1}   -0.16{col 64}{space 3}0.871{col 72}{space 4}-.3434595{col 85}{space 3} .2907711
{txt}{space 24}africa {c |}{col 32}{res}{space 2} -.136936{col 44}{space 2} .1948789{col 55}{space 1}   -0.70{col 64}{space 3}0.482{col 72}{space 4}-.5188917{col 85}{space 3} .2450197
{txt}{space 26}asia {c |}{col 32}{res}{space 2}-.2176287{col 44}{space 2} .2004313{col 55}{space 1}   -1.09{col 64}{space 3}0.278{col 72}{space 4}-.6104668{col 85}{space 3} .1752095
{txt}{space 24}europe {c |}{col 32}{res}{space 2} .6516851{col 44}{space 2} .1763251{col 55}{space 1}    3.70{col 64}{space 3}0.000{col 72}{space 4} .3060942{col 85}{space 3}  .997276
{txt}{space 15}time_kill_count {c |}{col 32}{res}{space 2} .0751028{col 44}{space 2} .0409399{col 55}{space 1}    1.83{col 64}{space 3}0.067{col 72}{space 4} -.005138{col 85}{space 3} .1553436
{txt}{space 18}time_kill_sq {c |}{col 32}{res}{space 2}-.0166184{col 44}{space 2} .0050374{col 55}{space 1}   -3.30{col 64}{space 3}0.001{col 72}{space 4}-.0264914{col 85}{space 3}-.0067453
{txt}{space 17}time_kill_cub {c |}{col 32}{res}{space 2} .0006066{col 44}{space 2} .0001506{col 55}{space 1}    4.03{col 64}{space 3}0.000{col 72}{space 4} .0003114{col 85}{space 3} .0009017
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} 2.709488{col 44}{space 2} .7135212{col 55}{space 1}    3.80{col 64}{space 3}0.000{col 72}{space 4} 1.311012{col 85}{space 3} 4.107963
{txt}{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}disap_imp                      {txt}{c |}
{space 21}disap_lag {c |}{col 32}{res}{space 2}-1.201067{col 44}{space 2} .0929152{col 55}{space 1}  -12.93{col 64}{space 3}0.000{col 72}{space 4}-1.383177{col 85}{space 3}-1.018956
{txt}{space 16}domestick1_lag {c |}{col 32}{res}{space 2} .0309199{col 44}{space 2} .1551726{col 55}{space 1}    0.20{col 64}{space 3}0.842{col 72}{space 4}-.2732129{col 85}{space 3} .3350526
{txt}{space 9}domestick1_lag_two_yr {c |}{col 32}{res}{space 2} .1175396{col 44}{space 2} .1741713{col 55}{space 1}    0.67{col 64}{space 3}0.500{col 72}{space 4}-.2238298{col 85}{space 3} .4589091
{txt}{space 19}polity2_lag {c |}{col 32}{res}{space 2}-.0081453{col 44}{space 2} .0147075{col 55}{space 1}   -0.55{col 64}{space 3}0.580{col 72}{space 4}-.0369715{col 85}{space 3} .0206809
{txt}{space 18}ln_gdppc_lag {c |}{col 32}{res}{space 2}  .024391{col 44}{space 2} .0636073{col 55}{space 1}    0.38{col 64}{space 3}0.701{col 72}{space 4} -.100277{col 85}{space 3} .1490591
{txt}{space 13}ln_population_lag {c |}{col 32}{res}{space 2}-.1356349{col 44}{space 2} .0439692{col 55}{space 1}   -3.08{col 64}{space 3}0.002{col 72}{space 4}-.2218129{col 85}{space 3}-.0494568
{txt}{space 23}lji_lag {c |}{col 32}{res}{space 2} .1467975{col 44}{space 2} .4527773{col 55}{space 1}    0.32{col 64}{space 3}0.746{col 72}{space 4}-.7406297{col 85}{space 3} 1.034225
{txt}{space 17}high_conflict {c |}{col 32}{res}{space 2}-.8587678{col 44}{space 2} .1737742{col 55}{space 1}   -4.94{col 64}{space 3}0.000{col 72}{space 4}-1.199359{col 85}{space 3}-.5181766
{txt}{space 15}djamnestyk1_lag {c |}{col 32}{res}{space 2}-.0143532{col 44}{space 2} .1392171{col 55}{space 1}   -0.10{col 64}{space 3}0.918{col 72}{space 4}-.2872137{col 85}{space 3} .2585072
{txt}{space 19}truthk1_lag {c |}{col 32}{res}{space 2} .6165533{col 44}{space 2} .2081845{col 55}{space 1}    2.96{col 64}{space 3}0.003{col 72}{space 4} .2085192{col 85}{space 3} 1.024587
{txt}{space 23}cat_rat {c |}{col 32}{res}{space 2}  .046383{col 44}{space 2} .1372338{col 55}{space 1}    0.34{col 64}{space 3}0.735{col 72}{space 4}-.2225903{col 85}{space 3} .3153562
{txt}{space 22}ccpr_rat {c |}{col 32}{res}{space 2}-.1866296{col 44}{space 2} .1864273{col 55}{space 1}   -1.00{col 64}{space 3}0.317{col 72}{space 4}-.5520204{col 85}{space 3} .1787612
{txt}{space 24}africa {c |}{col 32}{res}{space 2} .2376099{col 44}{space 2} .2088873{col 55}{space 1}    1.14{col 64}{space 3}0.255{col 72}{space 4}-.1718016{col 85}{space 3} .6470214
{txt}{space 26}asia {c |}{col 32}{res}{space 2} .0186352{col 44}{space 2} .2224512{col 55}{space 1}    0.08{col 64}{space 3}0.933{col 72}{space 4}-.4173611{col 85}{space 3} .4546316
{txt}{space 24}europe {c |}{col 32}{res}{space 2}-.3917713{col 44}{space 2} .4198979{col 55}{space 1}   -0.93{col 64}{space 3}0.351{col 72}{space 4}-1.214756{col 85}{space 3} .4312135
{txt}{space 14}time_disap_count {c |}{col 32}{res}{space 2} .0313234{col 44}{space 2} .0380626{col 55}{space 1}    0.82{col 64}{space 3}0.411{col 72}{space 4}-.0432779{col 85}{space 3} .1059246
{txt}{space 17}time_disap_sq {c |}{col 32}{res}{space 2}-.0060947{col 44}{space 2} .0041668{col 55}{space 1}   -1.46{col 64}{space 3}0.144{col 72}{space 4}-.0142614{col 85}{space 3}  .002072
{txt}{space 16}time_disap_cub {c |}{col 32}{res}{space 2}  .000147{col 44}{space 2} .0001087{col 55}{space 1}    1.35{col 64}{space 3}0.176{col 72}{space 4} -.000066{col 85}{space 3}   .00036
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} 2.497773{col 44}{space 2} .8679366{col 55}{space 1}    2.88{col 64}{space 3}0.004{col 72}{space 4} .7966484{col 85}{space 3} 4.198897
{txt}{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}loser_both_targ_trial          {txt}{c |}
{space 19}polity2_lag {c |}{col 32}{res}{space 2} .0195897{col 44}{space 2} .0173498{col 55}{space 1}    1.13{col 64}{space 3}0.259{col 72}{space 4}-.0144153{col 85}{space 3} .0535947
{txt}{space 18}ln_gdppc_lag {c |}{col 32}{res}{space 2}-.0632491{col 44}{space 2} .0612219{col 55}{space 1}   -1.03{col 64}{space 3}0.302{col 72}{space 4}-.1832419{col 85}{space 3} .0567437
{txt}{space 15}djamnestyk1_lag {c |}{col 32}{res}{space 2}-.2499825{col 44}{space 2} .2473319{col 55}{space 1}   -1.01{col 64}{space 3}0.312{col 72}{space 4}-.7347441{col 85}{space 3} .2347791
{txt}{space 19}truthk1_lag {c |}{col 32}{res}{space 2} .8036656{col 44}{space 2} .3099315{col 55}{space 1}    2.59{col 64}{space 3}0.010{col 72}{space 4}  .196211{col 85}{space 3}  1.41112
{txt}{space 23}lji_lag {c |}{col 32}{res}{space 2}-1.289867{col 44}{space 2} .5139667{col 55}{space 1}   -2.51{col 64}{space 3}0.012{col 72}{space 4}-2.297223{col 85}{space 3}-.2825105
{txt}{space 7}prev_conflict_intensity {c |}{col 32}{res}{space 2} .1430663{col 44}{space 2}  .121856{col 55}{space 1}    1.17{col 64}{space 3}0.240{col 72}{space 4}-.0957671{col 85}{space 3} .3818997
{txt}{space 23}cat_rat {c |}{col 32}{res}{space 2}-.0579015{col 44}{space 2} .2100229{col 55}{space 1}   -0.28{col 64}{space 3}0.783{col 72}{space 4}-.4695388{col 85}{space 3} .3537358
{txt}{space 22}ccpr_rat {c |}{col 32}{res}{space 2}-.0431358{col 44}{space 2} .1906448{col 55}{space 1}   -0.23{col 64}{space 3}0.821{col 72}{space 4}-.4167929{col 85}{space 3} .3305212
{txt}{space 4}time_targ_loser_both_count {c |}{col 32}{res}{space 2} -.144899{col 44}{space 2} .0458485{col 55}{space 1}   -3.16{col 64}{space 3}0.002{col 72}{space 4}-.2347604{col 85}{space 3}-.0550376
{txt}{space 1}time_targ_loser_both_count_sq {c |}{col 32}{res}{space 2} .0089096{col 44}{space 2} .0040409{col 55}{space 1}    2.20{col 64}{space 3}0.027{col 72}{space 4} .0009896{col 85}{space 3} .0168297
{txt}time_targ_loser_both_count_cub {c |}{col 32}{res}{space 2}-.0001652{col 44}{space 2} .0000944{col 55}{space 1}   -1.75{col 64}{space 3}0.080{col 72}{space 4}-.0003503{col 85}{space 3} .0000198
{txt}{space 25}_cons {c |}{col 32}{res}{space 2}-.5963399{col 44}{space 2} .5073015{col 55}{space 1}   -1.18{col 64}{space 3}0.240{col 72}{space 4}-1.590633{col 85}{space 3} .3979528
{txt}{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{col 1}{text}    /atrho21{col 14}{c |}{result}{space 2} .2614239{col 26}{space 2}    .0574{col 37}{space 1}    4.55{col 46}{space 3}0.000{col 55}{space 3}  .148922{col 67}{space 3} .3739258
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho31{col 14}{c |}{result}{space 2} .2564056{col 26}{space 2} .0582851{col 37}{space 1}    4.40{col 46}{space 3}0.000{col 55}{space 3}  .142169{col 67}{space 3} .3706423
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho41{col 14}{c |}{result}{space 2} .0472896{col 26}{space 2} .0645229{col 37}{space 1}    0.73{col 46}{space 3}0.464{col 55}{space 3} -.079173{col 67}{space 3} .1737523
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho51{col 14}{c |}{result}{space 2}-.1368796{col 26}{space 2} .0793855{col 37}{space 1}   -1.72{col 46}{space 3}0.085{col 55}{space 3}-.2924722{col 67}{space 3} .0187131
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho32{col 14}{c |}{result}{space 2} .2561201{col 26}{space 2} .0610409{col 37}{space 1}    4.20{col 46}{space 3}0.000{col 55}{space 3} .1364822{col 67}{space 3}  .375758
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho42{col 14}{c |}{result}{space 2} .0714581{col 26}{space 2} .0721692{col 37}{space 1}    0.99{col 46}{space 3}0.322{col 55}{space 3} -.069991{col 67}{space 3} .2129072
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho52{col 14}{c |}{result}{space 2}-.0253791{col 26}{space 2} .0925107{col 37}{space 1}   -0.27{col 46}{space 3}0.784{col 55}{space 3}-.2066968{col 67}{space 3} .1559386
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho43{col 14}{c |}{result}{space 2} .5008805{col 26}{space 2} .0732732{col 37}{space 1}    6.84{col 46}{space 3}0.000{col 55}{space 3} .3572678{col 67}{space 3} .6444933
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho53{col 14}{c |}{result}{space 2}-.0629773{col 26}{space 2} .0924869{col 37}{space 1}   -0.68{col 46}{space 3}0.496{col 55}{space 3}-.2442484{col 67}{space 3} .1182937
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho54{col 14}{c |}{result}{space 2} .0121347{col 26}{space 2} .0881069{col 37}{space 1}    0.14{col 46}{space 3}0.890{col 55}{space 3}-.1605518{col 67}{space 3} .1848211
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho21{col 14}{c |}{result}{space 2} .2556269{col 26}{space 2} .0536492{col 37}{space 1}    4.76{col 46}{space 3}0.000{col 55}{space 3} .1478308{col 67}{space 3} .3574208
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho31{col 14}{c |}{result}{space 2} .2509305{col 26}{space 2} .0546151{col 37}{space 1}    4.59{col 46}{space 3}0.000{col 55}{space 3} .1412188{col 67}{space 3} .3545534
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho41{col 14}{c |}{result}{space 2} .0472544{col 26}{space 2} .0643789{col 37}{space 1}    0.73{col 46}{space 3}0.463{col 55}{space 3} -.079008{col 67}{space 3} .1720246
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho51{col 14}{c |}{result}{space 2}-.1360311{col 26}{space 2} .0779165{col 37}{space 1}   -1.75{col 46}{space 3}0.081{col 55}{space 3}-.2844086{col 67}{space 3} .0187109
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho32{col 14}{c |}{result}{space 2}  .250663{col 26}{space 2} .0572056{col 37}{space 1}    4.38{col 46}{space 3}0.000{col 55}{space 3} .1356411{col 67}{space 3} .3590179
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho42{col 14}{c |}{result}{space 2} .0713367{col 26}{space 2}  .071802{col 37}{space 1}    0.99{col 46}{space 3}0.320{col 55}{space 3}-.0698769{col 67}{space 3} .2097475
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho52{col 14}{c |}{result}{space 2}-.0253737{col 26}{space 2} .0924512{col 37}{space 1}   -0.27{col 46}{space 3}0.784{col 55}{space 3}-.2038027{col 67}{space 3} .1546868
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho43{col 14}{c |}{result}{space 2} .4628094{col 26}{space 2} .0575786{col 37}{space 1}    8.04{col 46}{space 3}0.000{col 55}{space 3} .3428051{col 67}{space 3} .5679512
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho53{col 14}{c |}{result}{space 2}-.0628942{col 26}{space 2} .0921211{col 37}{space 1}   -0.68{col 46}{space 3}0.495{col 55}{space 3}-.2395045{col 67}{space 3}  .117745
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho54{col 14}{c |}{result}{space 2} .0121341{col 26}{space 2}  .088094{col 37}{space 1}    0.14{col 46}{space 3}0.890{col 55}{space 3}-.1591863{col 67}{space 3}  .182745
{txt}{hline 13}{c BT}{hline 64}
Likelihood ratio test of  rho21 = rho31 = rho41 = rho51 = rho32 = rho42 = rho52 = rho43 = rho53 = rho54 = 0:  
             chi2({res}10{txt}) = {res} 107.324{txt}   Prob > chi2 = {res}0.0000
{txt}({res}est10{txt} stored)

{com}. 
. 
. 
. *No domestic courts equation -  table A4 
. eststo: mvprobit (polpris_imp=polpris_lag domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe time_polpris_count time_polpris_sq time_polpris_cub)  (tort_imp=tort_lag domestick1_lag domestick1_lag_two_yr  polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_tort_count time_tort_sq time_tort_cub) (kill_imp=kill_lag domestick1_lag  domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_kill_count time_kill_sq time_kill_cub) (disap_imp=disap_lag  domestick1_lag  domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_disap_count time_disap_sq time_disap_cub)  if all_conflict_exp==1, cluster(cowcode) dr(75)

{txt}Iteration 0:{col 16}log pseudolikelihood = {res}-2716.6127{txt}  
Iteration 1:{col 16}log pseudolikelihood = {res}-2666.7115{txt}  
Iteration 2:{col 16}log pseudolikelihood = {res}-2664.1173{txt}  
Iteration 3:{col 16}log pseudolikelihood = {res}-2664.1073{txt}  
Iteration 4:{col 16}log pseudolikelihood = {res}-2664.1073{txt}  
{res}
{txt}Multivariate probit (MSL, # draws = 75){col 51}Number of obs{col 67}= {res}      2041
{col 51}{txt}Wald chi2({res}72{txt}){col 67}= {res}   4195.35
{txt}Log pseudolikelihood = {res}-2664.1073{col 51}{txt}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 87:(Std. err. adjusted for {res:86} clusters in cowcode)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}polpris_imp           {txt}{c |}
{space 10}polpris_lag {c |}{col 23}{res}{space 2}-1.052394{col 35}{space 2} .0819477{col 46}{space 1}  -12.84{col 55}{space 3}0.000{col 63}{space 4}-1.213008{col 76}{space 3}-.8917791
{txt}{space 7}domestick1_lag {c |}{col 23}{res}{space 2} .4243622{col 35}{space 2} .1438904{col 46}{space 1}    2.95{col 55}{space 3}0.003{col 63}{space 4} .1423421{col 76}{space 3} .7063823
{txt}domestick1_lag_two_yr {c |}{col 23}{res}{space 2}-.2877933{col 35}{space 2} .2411355{col 46}{space 1}   -1.19{col 55}{space 3}0.233{col 63}{space 4}-.7604101{col 76}{space 3} .1848235
{txt}{space 10}polity2_lag {c |}{col 23}{res}{space 2} .0603967{col 35}{space 2} .0125238{col 46}{space 1}    4.82{col 55}{space 3}0.000{col 63}{space 4} .0358506{col 76}{space 3} .0849428
{txt}{space 9}ln_gdppc_lag {c |}{col 23}{res}{space 2}-.0801595{col 35}{space 2} .0628508{col 46}{space 1}   -1.28{col 55}{space 3}0.202{col 63}{space 4}-.2033448{col 76}{space 3} .0430259
{txt}{space 4}ln_population_lag {c |}{col 23}{res}{space 2}-.2039102{col 35}{space 2} .0365902{col 46}{space 1}   -5.57{col 55}{space 3}0.000{col 63}{space 4}-.2756257{col 76}{space 3}-.1321946
{txt}{space 14}lji_lag {c |}{col 23}{res}{space 2} .1474923{col 35}{space 2} .3499892{col 46}{space 1}    0.42{col 55}{space 3}0.673{col 63}{space 4}-.5384738{col 76}{space 3} .8334585
{txt}{space 8}high_conflict {c |}{col 23}{res}{space 2} -.515891{col 35}{space 2} .1701547{col 46}{space 1}   -3.03{col 55}{space 3}0.002{col 63}{space 4}-.8493881{col 76}{space 3} -.182394
{txt}{space 6}djamnestyk1_lag {c |}{col 23}{res}{space 2} .0608892{col 35}{space 2} .1362823{col 46}{space 1}    0.45{col 55}{space 3}0.655{col 63}{space 4}-.2062193{col 76}{space 3} .3279977
{txt}{space 10}truthk1_lag {c |}{col 23}{res}{space 2} .3833809{col 35}{space 2} .2719881{col 46}{space 1}    1.41{col 55}{space 3}0.159{col 63}{space 4} -.149706{col 76}{space 3} .9164677
{txt}{space 14}cat_rat {c |}{col 23}{res}{space 2}-.0289656{col 35}{space 2} .1094645{col 46}{space 1}   -0.26{col 55}{space 3}0.791{col 63}{space 4}-.2435122{col 76}{space 3} .1855809
{txt}{space 13}ccpr_rat {c |}{col 23}{res}{space 2}-.2908954{col 35}{space 2}  .137918{col 46}{space 1}   -2.11{col 55}{space 3}0.035{col 63}{space 4}-.5612097{col 76}{space 3}-.0205811
{txt}{space 15}africa {c |}{col 23}{res}{space 2}-.1207289{col 35}{space 2}  .165483{col 46}{space 1}   -0.73{col 55}{space 3}0.466{col 63}{space 4}-.4450696{col 76}{space 3} .2036118
{txt}{space 17}asia {c |}{col 23}{res}{space 2}-.4236662{col 35}{space 2} .1543493{col 46}{space 1}   -2.74{col 55}{space 3}0.006{col 63}{space 4}-.7261853{col 76}{space 3}-.1211472
{txt}{space 15}europe {c |}{col 23}{res}{space 2} .2113651{col 35}{space 2}  .224449{col 46}{space 1}    0.94{col 55}{space 3}0.346{col 63}{space 4}-.2285467{col 76}{space 3}  .651277
{txt}{space 3}time_polpris_count {c |}{col 23}{res}{space 2}-.0385659{col 35}{space 2}   .04125{col 46}{space 1}   -0.93{col 55}{space 3}0.350{col 63}{space 4}-.1194145{col 76}{space 3} .0422827
{txt}{space 6}time_polpris_sq {c |}{col 23}{res}{space 2}-.0005594{col 35}{space 2} .0048141{col 46}{space 1}   -0.12{col 55}{space 3}0.907{col 63}{space 4}-.0099948{col 76}{space 3} .0088761
{txt}{space 5}time_polpris_cub {c |}{col 23}{res}{space 2} .0000529{col 35}{space 2} .0001282{col 46}{space 1}    0.41{col 55}{space 3}0.680{col 63}{space 4}-.0001984{col 76}{space 3} .0003042
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 3.983215{col 35}{space 2} .7590212{col 46}{space 1}    5.25{col 55}{space 3}0.000{col 63}{space 4} 2.495561{col 76}{space 3} 5.470869
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}tort_imp              {txt}{c |}
{space 13}tort_lag {c |}{col 23}{res}{space 2}-1.104637{col 35}{space 2} .0948116{col 46}{space 1}  -11.65{col 55}{space 3}0.000{col 63}{space 4}-1.290464{col 76}{space 3}-.9188095
{txt}{space 7}domestick1_lag {c |}{col 23}{res}{space 2}-.2669164{col 35}{space 2} .2011118{col 46}{space 1}   -1.33{col 55}{space 3}0.184{col 63}{space 4}-.6610883{col 76}{space 3} .1272556
{txt}domestick1_lag_two_yr {c |}{col 23}{res}{space 2}-.3584624{col 35}{space 2} .1689641{col 46}{space 1}   -2.12{col 55}{space 3}0.034{col 63}{space 4}-.6896259{col 76}{space 3}-.0272989
{txt}{space 10}polity2_lag {c |}{col 23}{res}{space 2} .0082121{col 35}{space 2} .0143972{col 46}{space 1}    0.57{col 55}{space 3}0.568{col 63}{space 4}-.0200059{col 76}{space 3} .0364302
{txt}{space 9}ln_gdppc_lag {c |}{col 23}{res}{space 2}  .022891{col 35}{space 2} .0582547{col 46}{space 1}    0.39{col 55}{space 3}0.694{col 63}{space 4}-.0912862{col 76}{space 3} .1370682
{txt}{space 4}ln_population_lag {c |}{col 23}{res}{space 2}-.1510544{col 35}{space 2} .0369152{col 46}{space 1}   -4.09{col 55}{space 3}0.000{col 63}{space 4}-.2234068{col 76}{space 3} -.078702
{txt}{space 14}lji_lag {c |}{col 23}{res}{space 2} .6622471{col 35}{space 2} .3623302{col 46}{space 1}    1.83{col 55}{space 3}0.068{col 63}{space 4} -.047907{col 76}{space 3} 1.372401
{txt}{space 8}high_conflict {c |}{col 23}{res}{space 2} -.388162{col 35}{space 2} .1727767{col 46}{space 1}   -2.25{col 55}{space 3}0.025{col 63}{space 4}-.7267981{col 76}{space 3}-.0495259
{txt}{space 6}djamnestyk1_lag {c |}{col 23}{res}{space 2} .0286381{col 35}{space 2} .1411846{col 46}{space 1}    0.20{col 55}{space 3}0.839{col 63}{space 4}-.2480787{col 76}{space 3} .3053549
{txt}{space 10}truthk1_lag {c |}{col 23}{res}{space 2} .7144389{col 35}{space 2} .2606944{col 46}{space 1}    2.74{col 55}{space 3}0.006{col 63}{space 4} .2034873{col 76}{space 3} 1.225391
{txt}{space 14}cat_rat {c |}{col 23}{res}{space 2}-.3004021{col 35}{space 2} .1032603{col 46}{space 1}   -2.91{col 55}{space 3}0.004{col 63}{space 4}-.5027885{col 76}{space 3}-.0980157
{txt}{space 13}ccpr_rat {c |}{col 23}{res}{space 2}-.2469618{col 35}{space 2} .1152624{col 46}{space 1}   -2.14{col 55}{space 3}0.032{col 63}{space 4} -.472872{col 76}{space 3}-.0210515
{txt}{space 15}africa {c |}{col 23}{res}{space 2} .1082669{col 35}{space 2}  .149845{col 46}{space 1}    0.72{col 55}{space 3}0.470{col 63}{space 4}-.1854239{col 76}{space 3} .4019577
{txt}{space 17}asia {c |}{col 23}{res}{space 2}-.1576723{col 35}{space 2} .1637137{col 46}{space 1}   -0.96{col 55}{space 3}0.335{col 63}{space 4}-.4785453{col 76}{space 3} .1632007
{txt}{space 15}europe {c |}{col 23}{res}{space 2} .4949215{col 35}{space 2} .1627455{col 46}{space 1}    3.04{col 55}{space 3}0.002{col 63}{space 4} .1759462{col 76}{space 3} .8138968
{txt}{space 6}time_tort_count {c |}{col 23}{res}{space 2}-.0456322{col 35}{space 2} .0372696{col 46}{space 1}   -1.22{col 55}{space 3}0.221{col 63}{space 4}-.1186793{col 76}{space 3}  .027415
{txt}{space 9}time_tort_sq {c |}{col 23}{res}{space 2}-.0004723{col 35}{space 2} .0035299{col 46}{space 1}   -0.13{col 55}{space 3}0.894{col 63}{space 4}-.0073907{col 76}{space 3}  .006446
{txt}{space 8}time_tort_cub {c |}{col 23}{res}{space 2}  .000049{col 35}{space 2} .0000907{col 46}{space 1}    0.54{col 55}{space 3}0.589{col 63}{space 4}-.0001288{col 76}{space 3} .0002267
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.906445{col 35}{space 2} .7183252{col 46}{space 1}    2.65{col 55}{space 3}0.008{col 63}{space 4} .4985537{col 76}{space 3} 3.314337
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}kill_imp              {txt}{c |}
{space 13}kill_lag {c |}{col 23}{res}{space 2} -.992812{col 35}{space 2} .0849716{col 46}{space 1}  -11.68{col 55}{space 3}0.000{col 63}{space 4}-1.159353{col 76}{space 3}-.8262707
{txt}{space 7}domestick1_lag {c |}{col 23}{res}{space 2} .0450409{col 35}{space 2} .1649091{col 46}{space 1}    0.27{col 55}{space 3}0.785{col 63}{space 4} -.278175{col 76}{space 3} .3682569
{txt}domestick1_lag_two_yr {c |}{col 23}{res}{space 2}-.0345195{col 35}{space 2} .1755535{col 46}{space 1}   -0.20{col 55}{space 3}0.844{col 63}{space 4}-.3785981{col 76}{space 3} .3095591
{txt}{space 10}polity2_lag {c |}{col 23}{res}{space 2}-.0539262{col 35}{space 2} .0149999{col 46}{space 1}   -3.60{col 55}{space 3}0.000{col 63}{space 4}-.0833254{col 76}{space 3} -.024527
{txt}{space 9}ln_gdppc_lag {c |}{col 23}{res}{space 2}-.0603087{col 35}{space 2} .0623583{col 46}{space 1}   -0.97{col 55}{space 3}0.333{col 63}{space 4}-.1825288{col 76}{space 3} .0619114
{txt}{space 4}ln_population_lag {c |}{col 23}{res}{space 2}-.1677045{col 35}{space 2} .0353454{col 46}{space 1}   -4.74{col 55}{space 3}0.000{col 63}{space 4}-.2369803{col 76}{space 3}-.0984287
{txt}{space 14}lji_lag {c |}{col 23}{res}{space 2} 1.338418{col 35}{space 2}  .401272{col 46}{space 1}    3.34{col 55}{space 3}0.001{col 63}{space 4} .5519395{col 76}{space 3} 2.124897
{txt}{space 8}high_conflict {c |}{col 23}{res}{space 2}-.7992755{col 35}{space 2} .1380243{col 46}{space 1}   -5.79{col 55}{space 3}0.000{col 63}{space 4}-1.069798{col 76}{space 3}-.5287529
{txt}{space 6}djamnestyk1_lag {c |}{col 23}{res}{space 2}-.1743236{col 35}{space 2} .1567071{col 46}{space 1}   -1.11{col 55}{space 3}0.266{col 63}{space 4}-.4814639{col 76}{space 3} .1328168
{txt}{space 10}truthk1_lag {c |}{col 23}{res}{space 2} .0303376{col 35}{space 2} .2860131{col 46}{space 1}    0.11{col 55}{space 3}0.916{col 63}{space 4}-.5302378{col 76}{space 3}  .590913
{txt}{space 14}cat_rat {c |}{col 23}{res}{space 2}  .052263{col 35}{space 2} .1243823{col 46}{space 1}    0.42{col 55}{space 3}0.674{col 63}{space 4}-.1915218{col 76}{space 3} .2960477
{txt}{space 13}ccpr_rat {c |}{col 23}{res}{space 2}-.0268233{col 35}{space 2} .1616024{col 46}{space 1}   -0.17{col 55}{space 3}0.868{col 63}{space 4}-.3435581{col 76}{space 3} .2899115
{txt}{space 15}africa {c |}{col 23}{res}{space 2}-.1396185{col 35}{space 2} .1953039{col 46}{space 1}   -0.71{col 55}{space 3}0.475{col 63}{space 4}-.5224072{col 76}{space 3} .2431702
{txt}{space 17}asia {c |}{col 23}{res}{space 2}-.2173458{col 35}{space 2} .2002267{col 46}{space 1}   -1.09{col 55}{space 3}0.278{col 63}{space 4} -.609783{col 76}{space 3} .1750914
{txt}{space 15}europe {c |}{col 23}{res}{space 2} .6473413{col 35}{space 2} .1770479{col 46}{space 1}    3.66{col 55}{space 3}0.000{col 63}{space 4} .3003338{col 76}{space 3} .9943487
{txt}{space 6}time_kill_count {c |}{col 23}{res}{space 2} .0764849{col 35}{space 2} .0405304{col 46}{space 1}    1.89{col 55}{space 3}0.059{col 63}{space 4}-.0029532{col 76}{space 3}  .155923
{txt}{space 9}time_kill_sq {c |}{col 23}{res}{space 2}-.0167621{col 35}{space 2} .0049988{col 46}{space 1}   -3.35{col 55}{space 3}0.001{col 63}{space 4}-.0265596{col 76}{space 3}-.0069646
{txt}{space 8}time_kill_cub {c |}{col 23}{res}{space 2} .0006099{col 35}{space 2} .0001498{col 46}{space 1}    4.07{col 55}{space 3}0.000{col 63}{space 4} .0003163{col 76}{space 3} .0009034
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.701823{col 35}{space 2} .7131404{col 46}{space 1}    3.79{col 55}{space 3}0.000{col 63}{space 4} 1.304093{col 76}{space 3} 4.099552
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}disap_imp             {txt}{c |}
{space 12}disap_lag {c |}{col 23}{res}{space 2} -1.20148{col 35}{space 2} .0924839{col 46}{space 1}  -12.99{col 55}{space 3}0.000{col 63}{space 4}-1.382745{col 76}{space 3}-1.020215
{txt}{space 7}domestick1_lag {c |}{col 23}{res}{space 2} .0303794{col 35}{space 2} .1549808{col 46}{space 1}    0.20{col 55}{space 3}0.845{col 63}{space 4}-.2733775{col 76}{space 3} .3341362
{txt}domestick1_lag_two_yr {c |}{col 23}{res}{space 2} .1178486{col 35}{space 2} .1730723{col 46}{space 1}    0.68{col 55}{space 3}0.496{col 63}{space 4} -.221367{col 76}{space 3} .4570641
{txt}{space 10}polity2_lag {c |}{col 23}{res}{space 2}-.0080871{col 35}{space 2} .0147858{col 46}{space 1}   -0.55{col 55}{space 3}0.584{col 63}{space 4}-.0370668{col 76}{space 3} .0208926
{txt}{space 9}ln_gdppc_lag {c |}{col 23}{res}{space 2} .0243922{col 35}{space 2} .0635614{col 46}{space 1}    0.38{col 55}{space 3}0.701{col 63}{space 4}-.1001858{col 76}{space 3} .1489703
{txt}{space 4}ln_population_lag {c |}{col 23}{res}{space 2} -.135662{col 35}{space 2} .0439142{col 46}{space 1}   -3.09{col 55}{space 3}0.002{col 63}{space 4}-.2217323{col 76}{space 3}-.0495917
{txt}{space 14}lji_lag {c |}{col 23}{res}{space 2} .1440404{col 35}{space 2} .4569804{col 46}{space 1}    0.32{col 55}{space 3}0.753{col 63}{space 4}-.7516247{col 76}{space 3} 1.039705
{txt}{space 8}high_conflict {c |}{col 23}{res}{space 2}-.8586315{col 35}{space 2} .1744438{col 46}{space 1}   -4.92{col 55}{space 3}0.000{col 63}{space 4}-1.200535{col 76}{space 3}-.5167279
{txt}{space 6}djamnestyk1_lag {c |}{col 23}{res}{space 2}-.0154939{col 35}{space 2} .1398911{col 46}{space 1}   -0.11{col 55}{space 3}0.912{col 63}{space 4}-.2896754{col 76}{space 3} .2586877
{txt}{space 10}truthk1_lag {c |}{col 23}{res}{space 2} .6177452{col 35}{space 2} .2093725{col 46}{space 1}    2.95{col 55}{space 3}0.003{col 63}{space 4} .2073826{col 76}{space 3} 1.028108
{txt}{space 14}cat_rat {c |}{col 23}{res}{space 2} .0470774{col 35}{space 2} .1375948{col 46}{space 1}    0.34{col 55}{space 3}0.732{col 63}{space 4}-.2226035{col 76}{space 3} .3167583
{txt}{space 13}ccpr_rat {c |}{col 23}{res}{space 2}-.1868932{col 35}{space 2} .1866687{col 46}{space 1}   -1.00{col 55}{space 3}0.317{col 63}{space 4}-.5527572{col 76}{space 3} .1789708
{txt}{space 15}africa {c |}{col 23}{res}{space 2} .2376299{col 35}{space 2} .2089861{col 46}{space 1}    1.14{col 55}{space 3}0.256{col 63}{space 4}-.1719754{col 76}{space 3} .6472352
{txt}{space 17}asia {c |}{col 23}{res}{space 2} .0186074{col 35}{space 2} .2227533{col 46}{space 1}    0.08{col 55}{space 3}0.933{col 63}{space 4}-.4179812{col 76}{space 3} .4551959
{txt}{space 15}europe {c |}{col 23}{res}{space 2}-.3878326{col 35}{space 2} .4189984{col 46}{space 1}   -0.93{col 55}{space 3}0.355{col 63}{space 4}-1.209054{col 76}{space 3} .4333891
{txt}{space 5}time_disap_count {c |}{col 23}{res}{space 2} .0307912{col 35}{space 2} .0377761{col 46}{space 1}    0.82{col 55}{space 3}0.415{col 63}{space 4}-.0432487{col 76}{space 3} .1048311
{txt}{space 8}time_disap_sq {c |}{col 23}{res}{space 2}-.0060427{col 35}{space 2} .0041342{col 46}{space 1}   -1.46{col 55}{space 3}0.144{col 63}{space 4}-.0141455{col 76}{space 3} .0020602
{txt}{space 7}time_disap_cub {c |}{col 23}{res}{space 2} .0001458{col 35}{space 2} .0001079{col 46}{space 1}    1.35{col 55}{space 3}0.177{col 63}{space 4}-.0000658{col 76}{space 3} .0003573
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.500557{col 35}{space 2} .8665751{col 46}{space 1}    2.89{col 55}{space 3}0.004{col 63}{space 4} .8021005{col 76}{space 3} 4.199012
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{col 1}{text}    /atrho21{col 14}{c |}{result}{space 2}  .259999{col 26}{space 2} .0574705{col 37}{space 1}    4.52{col 46}{space 3}0.000{col 55}{space 3}  .147359{col 67}{space 3}  .372639
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho31{col 14}{c |}{result}{space 2} .2555373{col 26}{space 2} .0584326{col 37}{space 1}    4.37{col 46}{space 3}0.000{col 55}{space 3} .1410115{col 67}{space 3} .3700632
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho41{col 14}{c |}{result}{space 2} .0484931{col 26}{space 2}  .064406{col 37}{space 1}    0.75{col 46}{space 3}0.451{col 55}{space 3}-.0777404{col 67}{space 3} .1747266
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho32{col 14}{c |}{result}{space 2} .2562395{col 26}{space 2} .0610848{col 37}{space 1}    4.19{col 46}{space 3}0.000{col 55}{space 3} .1365155{col 67}{space 3} .3759634
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho42{col 14}{c |}{result}{space 2} .0728604{col 26}{space 2} .0722256{col 37}{space 1}    1.01{col 46}{space 3}0.313{col 55}{space 3}-.0686991{col 67}{space 3}   .21442
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}    /atrho43{col 14}{c |}{result}{space 2} .5026289{col 26}{space 2} .0733099{col 37}{space 1}    6.86{col 46}{space 3}0.000{col 55}{space 3} .3589441{col 67}{space 3} .6463138
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho21{col 14}{c |}{result}{space 2} .2542946{col 26}{space 2} .0537541{col 37}{space 1}    4.73{col 46}{space 3}0.000{col 55}{space 3} .1463015{col 67}{space 3} .3562979
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho31{col 14}{c |}{result}{space 2} .2501167{col 26}{space 2} .0547772{col 37}{space 1}    4.57{col 46}{space 3}0.000{col 55}{space 3} .1400842{col 67}{space 3}  .354047
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho41{col 14}{c |}{result}{space 2} .0484551{col 26}{space 2} .0642548{col 37}{space 1}    0.75{col 46}{space 3}0.451{col 55}{space 3}-.0775842{col 67}{space 3}   .17297
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho32{col 14}{c |}{result}{space 2} .2507748{col 26}{space 2} .0572433{col 37}{space 1}    4.38{col 46}{space 3}0.000{col 55}{space 3} .1356737{col 67}{space 3} .3591968
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho42{col 14}{c |}{result}{space 2} .0727318{col 26}{space 2} .0718435{col 37}{space 1}    1.01{col 46}{space 3}0.311{col 55}{space 3}-.0685912{col 67}{space 3} .2111932
{txt}{hline 13}{c +}{hline 64}
{res}{col 1}{text}       rho43{col 14}{c |}{result}{space 2} .4641822{col 26}{space 2} .0575142{col 37}{space 1}    8.07{col 46}{space 3}0.000{col 55}{space 3} .3442837{col 67}{space 3} .5691832
{txt}{hline 13}{c BT}{hline 64}
Likelihood ratio test of  rho21 = rho31 = rho41 = rho32 = rho42 = rho43 = 0:  
             chi2({res}6{txt}) = {res} 105.011{txt}   Prob > chi2 = {res}0.0000
{txt}({res}est11{txt} stored)

{com}. 
. 
. *single equation models with counts of trials -Table A6*
. eststo: probit physint_imp physint_lag domestick1_count_lag  polity2_lag ln_gdppc_lag ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe time_physint_imp_count time_physint_sq  time_physint_cub if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-1279.3501
{txt}Iteration 1:   log pseudolikelihood = {res}-1161.7518
{txt}Iteration 2:   log pseudolikelihood = {res}-1160.5207
{txt}Iteration 3:   log pseudolikelihood = {res}-1160.5201

{txt}Probit regression                                 Number of obs   = {res}      2041
                                                  {txt}Wald chi2({res}17{txt})   = {res}    251.78
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-1160.5201                 {txt}Pseudo R2       = {res}    0.0929

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
 physint_imp {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
 physint_lag {c |}  {res}-.2404667   .0240497   -10.00   0.000    -.2876033   -.1933301
{txt}domest~t_lag {c |}  {res}  .084857   .0753473     1.13   0.260     -.062821     .232535
 {txt}polity2_lag {c |}  {res} .0090413   .0099543     0.91   0.364    -.0104689    .0285514
{txt}ln_gdppc_lag {c |}  {res}-.0267876   .0438892    -0.61   0.542    -.1128089    .0592337
{txt}ln_populat~g {c |}  {res}-.1654649    .033571    -4.93   0.000    -.2312628    -.099667
     {txt}lji_lag {c |}  {res} .2995753   .2956384     1.01   0.311    -.2798653    .8790159
{txt}high_confl~t {c |}  {res}-.7669033   .1401319    -5.47   0.000    -1.041557   -.4922498
{txt}djamne~1_lag {c |}  {res}-.1251369   .1274713    -0.98   0.326     -.374976    .1247023
 {txt}truthk1_lag {c |}  {res} .1681805   .1898941     0.89   0.376    -.2040051    .5403661
     {txt}cat_rat {c |}  {res}-.0677533   .0847698    -0.80   0.424    -.2338991    .0983925
    {txt}ccpr_rat {c |}  {res}-.2384811   .1018661    -2.34   0.019     -.438135   -.0388271
      {txt}africa {c |}  {res}-.0785243   .1214639    -0.65   0.518    -.3165892    .1595405
        {txt}asia {c |}  {res}-.2237943   .1367874    -1.64   0.102    -.4918926     .044304
      {txt}europe {c |}  {res} .4157007   .1231127     3.38   0.001     .1744042    .6569971
{txt}time_physi~t {c |}  {res} .1719394   .0453954     3.79   0.000      .082966    .2609127
{txt}time_physi~q {c |}  {res}-.0231319   .0086096    -2.69   0.007    -.0400063   -.0062574
{txt}time_physi~b {c |}  {res} .0007534   .0002948     2.56   0.011     .0001756    .0013313
       {txt}_cons {c |}  {res} 3.355594   .5450832     6.16   0.000     2.287251    4.423937
{txt}{hline 13}{c BT}{hline 64}
({res}est12{txt} stored)

{com}. 
. eststo: probit polpris_imp polpris_lag domestick1_count_lag   polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_polpris_count time_polpris_sq time_polpris_cub if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-856.47669
{txt}Iteration 1:   log pseudolikelihood = {res}-710.04112
{txt}Iteration 2:   log pseudolikelihood = {res}-702.67083
{txt}Iteration 3:   log pseudolikelihood = {res}-702.54873
{txt}Iteration 4:   log pseudolikelihood = {res}-702.54868

{txt}Probit regression                                 Number of obs   = {res}      2047
                                                  {txt}Wald chi2({res}17{txt})   = {res}    270.41
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-702.54868                 {txt}Pseudo R2       = {res}    0.1797

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
 polpris_imp {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
 polpris_lag {c |}  {res}-1.071857   .0829453   -12.92   0.000    -1.234427   -.9092876
{txt}domest~t_lag {c |}  {res} .3963826   .0861653     4.60   0.000     .2275017    .5652636
 {txt}polity2_lag {c |}  {res} .0597796   .0125937     4.75   0.000     .0350964    .0844627
{txt}ln_gdppc_lag {c |}  {res}-.0852637   .0624381    -1.37   0.172    -.2076401    .0371128
{txt}ln_populat~g {c |}  {res}-.2072675   .0370864    -5.59   0.000    -.2799555   -.1345795
     {txt}lji_lag {c |}  {res} .1964703   .3527601     0.56   0.578    -.4949268    .8878675
{txt}high_confl~t {c |}  {res}-.5208805   .1709188    -3.05   0.002    -.8558752   -.1858858
{txt}djamne~1_lag {c |}  {res}  .073052   .1382219     0.53   0.597     -.197858     .343962
 {txt}truthk1_lag {c |}  {res} .3577644   .2631665     1.36   0.174    -.1580324    .8735612
     {txt}cat_rat {c |}  {res}-.0245663    .109966    -0.22   0.823    -.2400958    .1909631
    {txt}ccpr_rat {c |}  {res} -.289959   .1355185    -2.14   0.032    -.5555705   -.0243476
      {txt}africa {c |}  {res}-.1307602   .1657296    -0.79   0.430    -.4555842    .1940638
        {txt}asia {c |}  {res}-.4293061   .1554513    -2.76   0.006     -.733985   -.1246273
      {txt}europe {c |}  {res} .1802492   .2188944     0.82   0.410    -.2487759    .6092744
{txt}time~s_count {c |}  {res}-.0490729   .0416768    -1.18   0.239    -.1307579    .0326121
{txt}time_po~s_sq {c |}  {res} 7.56e-06   .0048952     0.00   0.999    -.0095868     .009602
{txt}time_p~s_cub {c |}  {res} .0000414   .0001309     0.32   0.752    -.0002151     .000298
       {txt}_cons {c |}  {res} 4.088451   .7582822     5.39   0.000     2.602245    5.574657
{txt}{hline 13}{c BT}{hline 64}
({res}est13{txt} stored)

{com}. 
. eststo: probit tort_imp tort_lag domestick1_count_lag  polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_tort_count time_tort_sq time_tort_cub if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-791.69708
{txt}Iteration 1:   log pseudolikelihood = {res}-684.40301
{txt}Iteration 2:   log pseudolikelihood = {res}-678.93468
{txt}Iteration 3:   log pseudolikelihood = {res}-678.85883
{txt}Iteration 4:   log pseudolikelihood = {res}-678.85881

{txt}Probit regression                                 Number of obs   = {res}      2054
                                                  {txt}Wald chi2({res}17{txt})   = {res}    246.61
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-678.85881                 {txt}Pseudo R2       = {res}    0.1425

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
    tort_imp {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
    tort_lag {c |}  {res}-1.073001   .0948663   -11.31   0.000    -1.258936   -.8870665
{txt}domest~t_lag {c |}  {res}-.1990261   .1667894    -1.19   0.233    -.5259274    .1278752
 {txt}polity2_lag {c |}  {res} .0056822   .0139955     0.41   0.685    -.0217486    .0331129
{txt}ln_gdppc_lag {c |}  {res} .0178516   .0578444     0.31   0.758    -.0955213    .1312245
{txt}ln_populat~g {c |}  {res}-.1516537   .0372686    -4.07   0.000    -.2246987   -.0786087
     {txt}lji_lag {c |}  {res} .7021104   .3566524     1.97   0.049     .0030846    1.401136
{txt}high_confl~t {c |}  {res}-.3797444   .1741283    -2.18   0.029    -.7210296   -.0384592
{txt}djamne~1_lag {c |}  {res} .0416826   .1389059     0.30   0.764    -.2305679    .3139331
 {txt}truthk1_lag {c |}  {res} .6690574   .2668946     2.51   0.012     .1459536    1.192161
     {txt}cat_rat {c |}  {res}-.2797763   .1006085    -2.78   0.005    -.4769654   -.0825872
    {txt}ccpr_rat {c |}  {res}-.2205904   .1122791    -1.96   0.049    -.4406535   -.0005274
      {txt}africa {c |}  {res} .1177718   .1475532     0.80   0.425    -.1714271    .4069708
        {txt}asia {c |}  {res}-.1431254   .1599699    -0.89   0.371    -.4566607    .1704099
      {txt}europe {c |}  {res}  .482921   .1569687     3.08   0.002      .175268     .790574
{txt}time~t_count {c |}  {res}-.0478404   .0377185    -1.27   0.205    -.1217673    .0260866
{txt}time_tort_sq {c |}  {res}-.0003409   .0035469    -0.10   0.923    -.0072927     .006611
{txt}time_~rt_cub {c |}  {res} .0000417    .000092     0.45   0.651    -.0001386     .000222
       {txt}_cons {c |}  {res} 1.877564   .7168042     2.62   0.009     .4726533    3.282474
{txt}{hline 13}{c BT}{hline 64}
({res}est14{txt} stored)

{com}. 
. eststo: probit kill_imp kill_lag domestick1_count_lag   polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_kill_count time_kill_sq time_kill_cub if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-911.56311
{txt}Iteration 1:   log pseudolikelihood = {res}-778.92006
{txt}Iteration 2:   log pseudolikelihood = {res}-772.91111
{txt}Iteration 3:   log pseudolikelihood = {res}-772.84553
{txt}Iteration 4:   log pseudolikelihood = {res}-772.84552

{txt}Probit regression                                 Number of obs   = {res}      2052
                                                  {txt}Wald chi2({res}17{txt})   = {res}    189.88
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-772.84552                 {txt}Pseudo R2       = {res}    0.1522

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
    kill_imp {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
    kill_lag {c |}  {res} -.959507   .0887137   -10.82   0.000    -1.133383   -.7856313
{txt}domest~t_lag {c |}  {res}-.0152334   .1216386    -0.13   0.900    -.2536406    .2231739
 {txt}polity2_lag {c |}  {res}-.0533189   .0146065    -3.65   0.000    -.0819471   -.0246907
{txt}ln_gdppc_lag {c |}  {res}-.0729504   .0615275    -1.19   0.236    -.1935421    .0476414
{txt}ln_populat~g {c |}  {res}-.1622928   .0355126    -4.57   0.000    -.2318962   -.0926894
     {txt}lji_lag {c |}  {res} 1.343406   .3907782     3.44   0.001     .5774949    2.109317
{txt}high_confl~t {c |}  {res}-.7382889   .1368446    -5.40   0.000    -1.006499   -.4700784
{txt}djamne~1_lag {c |}  {res}-.1150724   .1485635    -0.77   0.439    -.4062515    .1761068
 {txt}truthk1_lag {c |}  {res} .1031647   .2839092     0.36   0.716    -.4532872    .6596165
     {txt}cat_rat {c |}  {res} .0586417   .1218102     0.48   0.630    -.1801019    .2973852
    {txt}ccpr_rat {c |}  {res}-.0233339   .1544782    -0.15   0.880    -.3261056    .2794379
      {txt}africa {c |}  {res}-.1511424   .1929396    -0.78   0.433    -.5292971    .2270122
        {txt}asia {c |}  {res}-.2354938   .1978519    -1.19   0.234    -.6232763    .1522888
      {txt}europe {c |}  {res} .6634818   .1714266     3.87   0.000     .3274919    .9994717
{txt}tim~ll_count {c |}  {res} .0721577    .043354     1.66   0.096    -.0128147      .15713
{txt}time_kill_sq {c |}  {res}-.0173561   .0054306    -3.20   0.001    -.0279999   -.0067122
{txt}time_k~l_cub {c |}  {res} .0006437   .0001647     3.91   0.000      .000321    .0009665
       {txt}_cons {c |}  {res} 2.682092   .7048452     3.81   0.000     1.300621    4.063563
{txt}{hline 13}{c BT}{hline 64}
({res}est15{txt} stored)

{com}. 
. eststo: probit disap_imp disap_lag  domestick1_count_lag  polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe  time_disap_count time_disap_sq time_disap_cub if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-802.48316
{txt}Iteration 1:   log pseudolikelihood = {res}-586.13084
{txt}Iteration 2:   log pseudolikelihood = {res}-570.97669
{txt}Iteration 3:   log pseudolikelihood = {res}-570.29869
{txt}Iteration 4:   log pseudolikelihood = {res}-570.29651
{txt}Iteration 5:   log pseudolikelihood = {res}-570.29651

{txt}Probit regression                                 Number of obs   = {res}      2050
                                                  {txt}Wald chi2({res}17{txt})   = {res}    295.61
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-570.29651                 {txt}Pseudo R2       = {res}    0.2893

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   disap_imp {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
   disap_lag {c |}  {res} -1.14776   .0977452   -11.74   0.000    -1.339337   -.9561824
{txt}domest~t_lag {c |}  {res}-.0648863   .1138468    -0.57   0.569    -.2880219    .1582493
 {txt}polity2_lag {c |}  {res}-.0084956   .0150085    -0.57   0.571    -.0379118    .0209205
{txt}ln_gdppc_lag {c |}  {res} .0103944   .0641391     0.16   0.871     -.115316    .1361048
{txt}ln_populat~g {c |}  {res}-.1297949   .0453014    -2.87   0.004    -.2185841   -.0410057
     {txt}lji_lag {c |}  {res} .1662161   .4499026     0.37   0.712    -.7155769    1.048009
{txt}high_confl~t {c |}  {res}-.7937423   .1687259    -4.70   0.000    -1.124439   -.4630456
{txt}djamne~1_lag {c |}  {res}-.0220333   .1428706    -0.15   0.877    -.3020545    .2579878
 {txt}truthk1_lag {c |}  {res} .6817517   .1944055     3.51   0.000      .300724    1.062779
     {txt}cat_rat {c |}  {res} .0530913   .1359543     0.39   0.696    -.2133743     .319557
    {txt}ccpr_rat {c |}  {res}-.1580952   .1806758    -0.88   0.382    -.5122133    .1960229
      {txt}africa {c |}  {res} .2252077   .2148462     1.05   0.295    -.1958831    .6462985
        {txt}asia {c |}  {res} .0092896   .2271556     0.04   0.967    -.4359273    .4545064
      {txt}europe {c |}  {res}-.3267471   .4099657    -0.80   0.425    -1.130265     .476771
{txt}tim~ap_count {c |}  {res} .0169099   .0409683     0.41   0.680    -.0633865    .0972062
{txt}time_di~p_sq {c |}  {res}-.0049938    .004537    -1.10   0.271    -.0138862    .0038985
{txt}time_d~p_cub {c |}  {res} .0001218   .0001169     1.04   0.297    -.0001074     .000351
       {txt}_cons {c |}  {res}  2.42494   .8680763     2.79   0.005     .7235415    4.126338
{txt}{hline 13}{c BT}{hline 64}
({res}est16{txt} stored)

{com}. 
. 
. 
. 
. 
. ***ordered probit models*** - Table A7 
. 
. *minimal*
. eststo: oprobit polpris domestick1_lag  polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict polpris_lag tort kill disap  if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-2186.6329
{txt}Iteration 1:   log pseudolikelihood = {res}-1382.4279
{txt}Iteration 2:   log pseudolikelihood = {res}-1334.8331
{txt}Iteration 3:   log pseudolikelihood = {res}-1333.0811
{txt}Iteration 4:   log pseudolikelihood = {res}-1333.0755

{txt}Ordered probit estimates                          Number of obs   = {res}      2045
                                                  {txt}Wald chi2({res}10{txt})   = {res}   1019.22
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-1333.0755                 {txt}Pseudo R2       = {res}    0.3904

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     polpris {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
domest~1_lag {c |}  {res}  .181835    .122222     1.49   0.137    -.0577156    .4213856
 {txt}polity2_lag {c |}  {res} .0693556   .0107315     6.46   0.000     .0483224    .0903889
{txt}ln_gdppc_lag {c |}  {res} .0060876   .0443836     0.14   0.891    -.0809026    .0930779
{txt}ln_populat~g {c |}  {res}-.1527533   .0343626    -4.45   0.000    -.2201028   -.0854039
     {txt}lji_lag {c |}  {res}-.2862057   .3706207    -0.77   0.440    -1.012609    .4401976
{txt}high_confl~t {c |}  {res}-.2347937   .1586957    -1.48   0.139    -.5458315    .0762442
 {txt}polpris_lag {c |}  {res} 1.141975   .0545282    20.94   0.000     1.035101    1.248848
        {txt}tort {c |}  {res} .2279484   .0723291     3.15   0.002      .086186    .3697108
        {txt}kill {c |}  {res} .1575146   .0685811     2.30   0.022     .0230981     .291931
       {txt}disap {c |}  {res} .0929945   .0649753     1.43   0.152    -.0343548    .2203438
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res}-1.584759   .6298359          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} .0552606   .6342803 
{txt}{hline 13}{c BT}{hline 64}
({res}est17{txt} stored)

{com}. eststo: oprobit tort domestick1_lag  polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict  tort_lag polpris kill disap if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-1698.2202
{txt}Iteration 1:   log pseudolikelihood = {res}-1212.5714
{txt}Iteration 2:   log pseudolikelihood = {res}-1192.4819
{txt}Iteration 3:   log pseudolikelihood = {res}-1192.1297
{txt}Iteration 4:   log pseudolikelihood = {res}-1192.1294

{txt}Ordered probit estimates                          Number of obs   = {res}      2049
                                                  {txt}Wald chi2({res}10{txt})   = {res}    424.23
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-1192.1294                 {txt}Pseudo R2       = {res}    0.2980

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        tort {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
domest~1_lag {c |}  {res}-.0855797   .1702709    -0.50   0.615    -.4193045    .2481451
 {txt}polity2_lag {c |}  {res}-.0066516   .0105503    -0.63   0.528    -.0273299    .0140266
{txt}ln_gdppc_lag {c |}  {res}-.0345481   .0413897    -0.83   0.404    -.1156704    .0465742
{txt}ln_populat~g {c |}  {res}-.0806761   .0307429    -2.62   0.009     -.140931   -.0204212
     {txt}lji_lag {c |}  {res} .6484521   .2993004     2.17   0.030     .0618341     1.23507
{txt}high_confl~t {c |}  {res} -.020531   .1690686    -0.12   0.903    -.3518993    .3108374
    {txt}tort_lag {c |}  {res} 1.036331   .0810429    12.79   0.000     .8774898    1.195172
     {txt}polpris {c |}  {res} .2252196   .0687707     3.27   0.001     .0904316    .3600076
        {txt}kill {c |}  {res} .4257884   .0563707     7.55   0.000     .3153039     .536273
       {txt}disap {c |}  {res} .0714564   .0551131     1.30   0.195    -.0365632    .1794761
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res} .1741383   .6231362          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} 2.170348   .6292092 
{txt}{hline 13}{c BT}{hline 64}
({res}est18{txt} stored)

{com}. eststo: oprobit kill domestick1_lag    polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict  kill_lag tort polpris disap if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res} -2227.833
{txt}Iteration 1:   log pseudolikelihood = {res}-1454.0613
{txt}Iteration 2:   log pseudolikelihood = {res}-1406.5551
{txt}Iteration 3:   log pseudolikelihood = {res}-1404.7824
{txt}Iteration 4:   log pseudolikelihood = {res}-1404.7774

{txt}Ordered probit estimates                          Number of obs   = {res}      2047
                                                  {txt}Wald chi2({res}10{txt})   = {res}   1180.07
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-1404.7774                 {txt}Pseudo R2       = {res}    0.3694

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        kill {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
domest~1_lag {c |}  {res}-.0244561   .1497154    -0.16   0.870    -.3178928    .2689806
 {txt}polity2_lag {c |}  {res}-.0422127    .011522    -3.66   0.000    -.0647954   -.0196299
{txt}ln_gdppc_lag {c |}  {res} .0735513   .0406573     1.81   0.070    -.0061356    .1532382
{txt}ln_populat~g {c |}  {res}-.0940329   .0347491    -2.71   0.007    -.1621399    -.025926
     {txt}lji_lag {c |}  {res} .7023403   .4734654     1.48   0.138     -.225635    1.630315
{txt}high_confl~t {c |}  {res} -.375264   .1131738    -3.32   0.001    -.5970804   -.1534475
    {txt}kill_lag {c |}  {res} 1.063834   .0816499    13.03   0.000     .9038034    1.223865
        {txt}tort {c |}  {res} .4276606   .0612663     6.98   0.000     .3075808    .5477404
     {txt}polpris {c |}  {res} .2006837   .0646867     3.10   0.002     .0739001    .3274674
       {txt}disap {c |}  {res}  .450977   .1100038     4.10   0.000     .2353735    .6665806
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res} .3461447    .584066          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} 2.244341   .5834876 
{txt}{hline 13}{c BT}{hline 64}
({res}est19{txt} stored)

{com}. eststo: oprobit disap domestick1_lag  polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict disap_lag kill tort polpris  if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res} -1883.229
{txt}Iteration 1:   log pseudolikelihood = {res}-1244.2735
{txt}Iteration 2:   log pseudolikelihood = {res}-1214.8275
{txt}Iteration 3:   log pseudolikelihood = {res}-1214.2495
{txt}Iteration 4:   log pseudolikelihood = {res} -1214.249

{txt}Ordered probit estimates                          Number of obs   = {res}      2047
                                                  {txt}Wald chi2({res}10{txt})   = {res}    623.15
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res} -1214.249                 {txt}Pseudo R2       = {res}    0.3552

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
       disap {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
domest~1_lag {c |}  {res} .0976576   .1193841     0.82   0.413     -.136331    .3316461
 {txt}polity2_lag {c |}  {res} .0174453   .0115302     1.51   0.130    -.0051535    .0400441
{txt}ln_gdppc_lag {c |}  {res}-.0137879   .0390913    -0.35   0.724    -.0904055    .0628297
{txt}ln_populat~g {c |}  {res}-.0698083   .0353318    -1.98   0.048    -.1390575   -.0005592
     {txt}lji_lag {c |}  {res}-.3221887    .462695    -0.70   0.486    -1.229054    .5846767
{txt}high_confl~t {c |}  {res}-.4683843   .1102462    -4.25   0.000     -.684463   -.2523057
   {txt}disap_lag {c |}  {res} 1.082243   .1131086     9.57   0.000      .860554    1.303932
        {txt}kill {c |}  {res}  .490518   .1010112     4.86   0.000     .2925397    .6884963
        {txt}tort {c |}  {res} .1055217   .0709081     1.49   0.137    -.0334557     .244499
     {txt}polpris {c |}  {res} .1275734   .0777322     1.64   0.101     -.024779    .2799258
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res}-.8276443   .6923349          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} .4188718   .7083828 
{txt}{hline 13}{c BT}{hline 64}
({res}est20{txt} stored)

{com}. *expansive*
. eststo: oprobit polpris domestick1_lag  domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe polpris_lag tort kill disap if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-2186.6329
{txt}Iteration 1:   log pseudolikelihood = {res} -1363.539
{txt}Iteration 2:   log pseudolikelihood = {res}-1310.5393
{txt}Iteration 3:   log pseudolikelihood = {res}-1308.3058
{txt}Iteration 4:   log pseudolikelihood = {res}-1308.2967
{txt}Iteration 5:   log pseudolikelihood = {res}-1308.2967

{txt}Ordered probit estimates                          Number of obs   = {res}      2045
                                                  {txt}Wald chi2({res}18{txt})   = {res}   1372.11
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-1308.2967                 {txt}Pseudo R2       = {res}    0.4017

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
     polpris {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
domest~1_lag {c |}  {res}  .155222   .1321615     1.17   0.240    -.1038097    .4142537
{txt}domestick1.. {c |}  {res}-.1977658   .1333788    -1.48   0.138    -.4591834    .0636517
 {txt}polity2_lag {c |}  {res} .0555956   .0119579     4.65   0.000     .0321585    .0790327
{txt}ln_gdppc_lag {c |}  {res}-.0699313   .0585642    -1.19   0.232    -.1847151    .0448524
{txt}ln_populat~g {c |}  {res}-.1111302   .0348861    -3.19   0.001    -.1795057   -.0427547
     {txt}lji_lag {c |}  {res} .0855417   .3154409     0.27   0.786    -.5327111    .7037944
{txt}high_confl~t {c |}  {res}-.2834957   .1691969    -1.68   0.094    -.6151155    .0481242
{txt}djamne~1_lag {c |}  {res} .1716401   .1110861     1.55   0.122    -.0460846    .3893647
 {txt}truthk1_lag {c |}  {res} .2777526   .2716868     1.02   0.307    -.2547438     .810249
     {txt}cat_rat {c |}  {res} .0755501   .0867601     0.87   0.384    -.0944966    .2455968
    {txt}ccpr_rat {c |}  {res}-.1474092   .1273498    -1.16   0.247    -.3970102    .1021917
      {txt}africa {c |}  {res}-.3104935    .142385    -2.18   0.029    -.5895629   -.0314241
        {txt}asia {c |}  {res}-.6238529   .1362072    -4.58   0.000    -.8908142   -.3568917
      {txt}europe {c |}  {res} .0251273   .2093287     0.12   0.904    -.3851494     .435404
 {txt}polpris_lag {c |}  {res} 1.095505   .0543329    20.16   0.000     .9890148    1.201996
        {txt}tort {c |}  {res} .2156846   .0679551     3.17   0.002     .0824951    .3488741
        {txt}kill {c |}  {res} .1372084      .0608     2.26   0.024     .0180427    .2563741
       {txt}disap {c |}  {res} .1167751   .0606014     1.93   0.054    -.0020015    .2355517
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res}-1.710172   .6871925          {txt}(Ancillary parameters)
       _cut2 {c |}  {res}-.0305535   .6925125 
{txt}{hline 13}{c BT}{hline 64}
({res}est21{txt} stored)

{com}. eststo: oprobit tort domestick1_lag domestick1_lag_two_yr   polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe tort_lag polpris kill disap if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res}-1698.2202
{txt}Iteration 1:   log pseudolikelihood = {res}-1195.7244
{txt}Iteration 2:   log pseudolikelihood = {res}-1172.1335
{txt}Iteration 3:   log pseudolikelihood = {res}-1171.6425
{txt}Iteration 4:   log pseudolikelihood = {res}-1171.6421

{txt}Ordered probit estimates                          Number of obs   = {res}      2049
                                                  {txt}Wald chi2({res}18{txt})   = {res}    484.19
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-1171.6421                 {txt}Pseudo R2       = {res}    0.3101

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        tort {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
domest~1_lag {c |}  {res}-.0870664    .169296    -0.51   0.607    -.4188804    .2447475
{txt}domestick1.. {c |}  {res}-.2370063   .1220194    -1.94   0.052    -.4761599    .0021473
 {txt}polity2_lag {c |}  {res} .0139461   .0118376     1.18   0.239    -.0092552    .0371474
{txt}ln_gdppc_lag {c |}  {res} .0279965   .0505837     0.55   0.580    -.0711458    .1271388
{txt}ln_populat~g {c |}  {res}-.0878611   .0347924    -2.53   0.012    -.1560529   -.0196692
     {txt}lji_lag {c |}  {res} .3338208   .3092869     1.08   0.280    -.2723704    .9400121
{txt}high_confl~t {c |}  {res}-.0399222   .1705489    -0.23   0.815     -.374192    .2943475
{txt}djamne~1_lag {c |}  {res} .0954839   .1282659     0.74   0.457    -.1559126    .3468805
 {txt}truthk1_lag {c |}  {res} .4600341   .2479511     1.86   0.064     -.025941    .9460093
     {txt}cat_rat {c |}  {res}-.3155068   .0994287    -3.17   0.002    -.5103834   -.1206301
    {txt}ccpr_rat {c |}  {res}-.2035479   .1069206    -1.90   0.057    -.4131084    .0060126
      {txt}africa {c |}  {res} .1838688   .1405884     1.31   0.191    -.0916795     .459417
        {txt}asia {c |}  {res} .1008513   .1674801     0.60   0.547    -.2274037    .4291063
      {txt}europe {c |}  {res} .0944614   .1692664     0.56   0.577    -.2372947    .4262174
    {txt}tort_lag {c |}  {res} .9847961   .0798336    12.34   0.000      .828325    1.141267
     {txt}polpris {c |}  {res} .2361087    .065592     3.60   0.000     .1075508    .3646666
        {txt}kill {c |}  {res} .4381874   .0583217     7.51   0.000     .3238789    .5524959
       {txt}disap {c |}  {res} .0861231    .055456     1.55   0.120    -.0225686    .1948148
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res} .1749026   .7134215          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} 2.202373   .7146738 
{txt}{hline 13}{c BT}{hline 64}
({res}est22{txt} stored)

{com}. eststo: oprobit kill domestick1_lag  domestick1_lag_two_yr  polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag cat_rat ccpr_rat africa asia europe kill_lag tort polpris disap if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res} -2227.833
{txt}Iteration 1:   log pseudolikelihood = {res}-1431.4277
{txt}Iteration 2:   log pseudolikelihood = {res} -1378.013
{txt}Iteration 3:   log pseudolikelihood = {res} -1375.756
{txt}Iteration 4:   log pseudolikelihood = {res}-1375.7479

{txt}Ordered probit estimates                          Number of obs   = {res}      2047
                                                  {txt}Wald chi2({res}18{txt})   = {res}   1072.16
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-1375.7479                 {txt}Pseudo R2       = {res}    0.3825

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        kill {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
domest~1_lag {c |}  {res}-.0919416   .1550638    -0.59   0.553     -.395861    .2119778
{txt}domestick1.. {c |}  {res} .1462815   .1255773     1.16   0.244    -.0998455    .3924085
 {txt}polity2_lag {c |}  {res}-.0569245   .0114091    -4.99   0.000     -.079286    -.034563
{txt}ln_gdppc_lag {c |}  {res}-.0362101   .0485238    -0.75   0.456    -.1313149    .0588948
{txt}ln_populat~g {c |}  {res}-.1276514   .0349954    -3.65   0.000    -.1962412   -.0590616
     {txt}lji_lag {c |}  {res} .9908495   .4055598     2.44   0.015      .195967    1.785732
{txt}high_confl~t {c |}  {res} -.404515   .1160675    -3.49   0.000    -.6320031   -.1770269
{txt}djamne~1_lag {c |}  {res}-.1784575   .1047329    -1.70   0.088    -.3837302    .0268153
 {txt}truthk1_lag {c |}  {res}-.1321542   .2493254    -0.53   0.596    -.6208229    .3565146
     {txt}cat_rat {c |}  {res} .0725872   .0982269     0.74   0.460    -.1199339    .2651083
    {txt}ccpr_rat {c |}  {res} .0655237   .1219112     0.54   0.591    -.1734178    .3044651
      {txt}africa {c |}  {res}-.1457483   .1417547    -1.03   0.304    -.4235825    .1320858
        {txt}asia {c |}  {res}-.0692313   .1425591    -0.49   0.627     -.348642    .2101794
      {txt}europe {c |}  {res} .8058407   .1856898     4.34   0.000     .4418955    1.169786
    {txt}kill_lag {c |}  {res} .9959199   .0725846    13.72   0.000     .8536567    1.138183
        {txt}tort {c |}  {res} .4297826   .0623129     6.90   0.000     .3076515    .5519137
     {txt}polpris {c |}  {res} .1474521   .0573178     2.57   0.010     .0351113    .2597928
       {txt}disap {c |}  {res} .4983802   .0850567     5.86   0.000     .3316721    .6650884
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res} -.879952   .6184394          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} 1.063958   .6229607 
{txt}{hline 13}{c BT}{hline 64}
({res}est23{txt} stored)

{com}. eststo: oprobit disap domestick1_lag domestick1_lag_two_yr polity2_lag ln_gdppc_lag  ln_population_lag  lji_lag high_conflict djamnestyk1_lag truthk1_lag  cat_rat ccpr_rat africa asia europe disap_lag kill tort polpris  if all_conflict_exp==1, cluster(cowcode)

{txt}Iteration 0:   log pseudolikelihood = {res} -1883.229
{txt}Iteration 1:   log pseudolikelihood = {res}-1236.7523
{txt}Iteration 2:   log pseudolikelihood = {res}-1205.2977
{txt}Iteration 3:   log pseudolikelihood = {res}-1204.6161
{txt}Iteration 4:   log pseudolikelihood = {res}-1204.6153

{txt}Ordered probit estimates                          Number of obs   = {res}      2047
                                                  {txt}Wald chi2({res}18{txt})   = {res}   1054.88
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-1204.6153                 {txt}Pseudo R2       = {res}    0.3603

                               {txt}(Std. err. adjusted for {res}86{txt} clusters in cowcode)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
       disap {c |} Coefficient  std. err.      z    P>|z|     [95% conf. interval]
{hline 13}{c +}{hline 64}
domest~1_lag {c |}  {res} .1324341   .1229692     1.08   0.281    -.1085811    .3734493
{txt}domestick1.. {c |}  {res} .0057312   .1398407     0.04   0.967    -.2683515    .2798139
 {txt}polity2_lag {c |}  {res}  .022846   .0124312     1.84   0.066    -.0015187    .0472107
{txt}ln_gdppc_lag {c |}  {res} .0535901   .0392774     1.36   0.172    -.0233922    .1305724
{txt}ln_populat~g {c |}  {res}-.0733427   .0379777    -1.93   0.053    -.1477776    .0010922
     {txt}lji_lag {c |}  {res}-.4631716   .4610525    -1.00   0.315    -1.366818    .4404748
{txt}high_confl~t {c |}  {res}-.4603059   .1196926    -3.85   0.000    -.6948991   -.2257128
{txt}djamne~1_lag {c |}  {res} -.147802   .0982136    -1.50   0.132     -.340297     .044693
 {txt}truthk1_lag {c |}  {res} .1548475   .3197218     0.48   0.628    -.4717958    .7814907
     {txt}cat_rat {c |}  {res} .1420849   .0913901     1.55   0.120    -.0370364    .3212062
    {txt}ccpr_rat {c |}  {res}-.0756287    .115919    -0.65   0.514    -.3028258    .1515683
      {txt}africa {c |}  {res} .2198776   .1491735     1.47   0.140    -.0724971    .5122523
        {txt}asia {c |}  {res} .1495902   .1381437     1.08   0.279    -.1211664    .4203469
      {txt}europe {c |}  {res}-.3780334   .3090395    -1.22   0.221    -.9837396    .2276728
   {txt}disap_lag {c |}  {res} 1.053208   .1046479    10.06   0.000     .8481022    1.258314
        {txt}kill {c |}  {res} .5313087   .0776247     6.84   0.000     .3791671    .6834502
        {txt}tort {c |}  {res} .1275597   .0722337     1.77   0.077    -.0140158    .2691351
     {txt}polpris {c |}  {res} .1636667   .0662014     2.47   0.013     .0339143     .293419
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res} -.316281   .6825161          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} .9455176   .6758341 
{txt}{hline 13}{c BT}{hline 64}
({res}est24{txt} stored)

{com}. 
. 
. 
. 
. log close 
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/sambell/Dropbox/Bell_Kitagawa/JCR Draft/JCR R&R/Data/Creating some new variables in TJ data - side analysis/Replication.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 5 Nov 2021, 13:14:55
{txt}{.-}
{smcl}
{txt}{sf}{ul off}